2024 Inference Jobs - Page 7

🧠 Job Title: Senior Machine Learning Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 4–8 years Education : B.Tech / M.Tech / Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or related fields 🚀 About Darwix AI Darwix AI is India's fastest-growing GenAI SaaS startup, building real-time conversational intelligence and agent-assist platforms that supercharge omnichannel enterprise sales teams across India, MENA, and Southeast Asia. Our mission is to redefine how revenue teams operate by using Generative AI, LLMs, Voice AI , and deep analytics to deliver better conversations, faster deal cycles, and consistent growth. Our flagship platform, Transform+ , analyzes millions of hours of sales conversations, gives live nudges, builds AI-powered sales content, and enables revenue teams to become truly data-driven — in real time. We’re backed by marquee investors, industry veterans, and AI experts, and we’re expanding fast. As a Senior Machine Learning Engineer , you will play a pivotal role in designing and deploying intelligent ML systems that power every layer of this platform — from speech-to-text, diarization, vector search, and summarization to recommendation engines and personalized insights. 🎯 Role Overview This is a high-impact, high-ownership role for someone who lives and breathes data, models, and real-world machine learning. You will design, train, fine-tune, deploy, and optimize ML models across various domains — speech, NLP, tabular, and ranking. Your work will directly power critical product features: from personalized agent nudges and conversation scoring to lead scoring, smart recommendations, and retrieval-augmented generation (RAG) pipelines. You’ll be the bridge between data science, engineering, and product — converting ideas into models, and models into production-scale systems with tangible business value. 🧪 Key Responsibilities🔬 1. Model Design, Training, and Optimization Develop and fine-tune machine learning models using structured, unstructured, and semi-structured data sources. Work with models across domains: text classification, speech transcription, named entity recognition, topic modeling, summarization, time series, and recommendation systems. Explore and implement transformer architectures, BERT-style encoders, Siamese networks, and retrieval-based models. 📊 2. Data Engineering & Feature Extraction Build robust ETL pipelines to clean, label, and enrich data for supervised and unsupervised learning tasks. Work with multimodal inputs — audio, text, metadata — and build smart representations for downstream tasks. Automate data collection from APIs, CRMs, sales transcripts, and call logs. ⚙️ 3. Productionizing ML Pipelines Package and deploy models in scalable APIs (using FastAPI, Flask, or similar frameworks). Work closely with DevOps to containerize and orchestrate ML workflows using Docker, Kubernetes, or CI/CD pipelines. Ensure production readiness: logging, monitoring, rollback, and fail-safes. 📈 4. Experimentation & Evaluation Design rigorous experiments using A/B tests, offline metrics, and post-deployment feedback loops. Continuously optimize model performance (latency, accuracy, precision-recall trade-offs). Implement drift detection and re-training pipelines for models in production. 🔁 5. Collaboration with Product & Engineering Translate business problems into ML problems and align modeling goals with user outcomes. Partner with product managers, AI researchers, data annotators, and frontend/backend engineers to build and launch features. Contribute to the product roadmap with ML-driven ideas and prototypes. 🛠️ 6. Innovation & Technical Leadership Evaluate open-source and proprietary LLM APIs, AutoML frameworks, vector databases, and model inference techniques. Drive innovation in voice-to-insight systems (ASR + Diarization + NLP). Mentor junior engineers and contribute to best practices in ML development and deployment. 🧰 Tech Stack🔧 Languages & Frameworks Python (core), SQL, Bash PyTorch, TensorFlow, HuggingFace, scikit-learn, XGBoost, LightGBM 🧠 ML & AI Ecosystem Transformers, RNNs, CNNs, CRFs BERT, RoBERTa, GPT-style models OpenAI API, Cohere, LLaMA, Mistral, Anthropic Claude FAISS, Pinecone, Qdrant, LlamaIndex ☁️ Deployment & Infrastructure Docker, Kubernetes, GitHub Actions, Jenkins AWS (EC2, Lambda, S3, SageMaker), GCP, Azure Redis, PostgreSQL, MongoDB 📊 Monitoring & Experimentation MLflow, Weights & Biases, TensorBoard, Prometheus, Grafana 👨‍💼 Qualifications🎓 Education Bachelor’s or Master’s degree in CS, AI, Statistics, or related quantitative disciplines. Certifications in advanced ML, data science, or AI are a plus. 🧑‍💻 Experience 4–8 years of hands-on experience in applied machine learning. Demonstrated success in deploying models to production at scale. Deep familiarity with transformer-based architectures and model evaluation. ✅ You’ll Excel In This Role If You… Thrive on solving end-to-end ML problems — not just notebooks, but deployment, testing, and iteration. Obsess over clean, maintainable, reusable code and pipelines. Think from first principles and challenge model assumptions when they don’t work. Are deeply curious and have built multiple projects just because you wanted to know how something works. Are comfortable working with ambiguity, fast timelines, and real-time data challenges. Want to build AI products that get used by real people and drive revenue outcomes — not just vanity demos. 💼 What You’ll Get at Darwix AI Work with some of the brightest minds in AI , product, and design. Solve AI problems that push the boundaries of real-time, voice-first, multilingual enterprise use cases. Direct mentorship from senior architects and AI scientists. Competitive compensation (₹30L–₹45L CTC) + ESOPs + rapid growth trajectory. Opportunity to shape the future of a global-first AI startup built from India. Hands-on experience with the most advanced tech stack in applied ML and production AI. Front-row seat to a generational company that is redefining enterprise AI. 📩 How to Apply Ready to build with us? Send your resume, GitHub/portfolio, and a short write-up on: “What’s the most interesting ML system you’ve built — and what made it work?” Email: people@darwix.ai Subject: Senior ML Engineer – Application 🔐 Final Notes We value speed, honesty, and humility. We ship fast, fail fast, and learn even faster. This role is designed for high-agency, hands-on ML engineers who want to make a difference — not just write code. If you’re looking for a role where you own real impact , push technical boundaries, and work with a team that’s as obsessed with AI as you are — then Darwix AI is the place for you. Darwix AI – GenAI for Revenue Teams. Built from India, for the World.

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Junior Data Scientist Location: Bangalore Reporting to: Senior Manager – Analytics Purpose of the role The Global GenAI Team at Anheuser-Busch InBev (AB InBev) is tasked with constructing competitive solutions utilizing GenAI techniques. These solutions aim to extract contextual insights and meaningful information from our enterprise data assets. The derived data-driven insights play a pivotal role in empowering our business users to make well-informed decisions regarding their respective products. In the role of a Machine Learning Engineer (MLE), you will operate at the intersection of: LLM-based frameworks, tools, and technologies Cloud-native technologies and solutions Microservices-based software architecture and design patterns As an additional responsibility, you will be involved in the complete development cycle of new product features, encompassing tasks such as the development and deployment of new models integrated into production systems. Furthermore, you will have the opportunity to critically assess and influence the product engineering, design, architecture, and technology stack across multiple products, extending beyond your immediate focus. Key tasks & accountabilities Large Language Models (LLM): Experience with LangChain, LangGraph Proficiency in building agentic patterns like ReAct, ReWoo, LLMCompiler Multi-modal Retrieval-Augmented Generation (RAG): Expertise in multi-modal AI systems (text, images, audio, video) Designing and optimizing chunking strategies and clustering for large data processing Streaming & Real-time Processing: Experience in audio/video streaming and real-time data pipelines Low-latency inference and deployment architectures NL2SQL: Natural language-driven SQL generation for databases Experience with natural language interfaces to databases and query optimization API Development: Building scalable APIs with FastAPI for AI model serving Containerization & Orchestration: Proficient with Docker for containerized AI services Experience with orchestration tools for deploying and managing services Data Processing & Pipelines: Experience with chunking strategies for efficient document processing Building data pipelines to handle large-scale data for AI model training and inference AI Frameworks & Tools: Experience with AI/ML frameworks like TensorFlow, PyTorch Proficiency in LangChain, LangGraph, and other LLM-related technologies Prompt Engineering: Expertise in advanced prompting techniques like Chain of Thought (CoT) prompting, LLM Judge, and self-reflection prompting Experience with prompt compression and optimization using tools like LLMLingua, AdaFlow, TextGrad, and DSPy Strong understanding of context window management and optimizing prompts for performance and efficiency Qualifications, Experience, Skills Level of educational attainment required (1 or more of the following) Bachelor's or masterʼs degree in Computer Science, Engineering, or a related field. Previous Work Experience Required Proven experience of 1+ years in developing and deploying applications utilizing Azure OpenAI and Redis as a vector database. Technical Skills Required Solid understanding of language model technologies, including LangChain, OpenAI Python SDK, LammaIndex, OLamma, etc. Proficiency in implementing and optimizing machine learning models for natural language processing. Experience with observability tools such as mlflow, langsmith, langfuse, weight and bias, etc. Strong programming skills in languages such as Python and proficiency in relevant frameworks. Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes). And above all of this, an undying love for beer! We dream big to create future with more cheer

We are hiring a Senior Software Development Engineer for our platform. We are helping enterprises and service providers build their AI inference platforms for end users. As a Senior Software Engineer, you will take ownership of backend-heavy, full-stack feature development—building robust services, scalable APIs, and intuitive frontends that power the user experience. You’ll contribute to the core of our enterprise-grade AI platform, collaborating across teams to ensure our systems are performant, secure, and built to last. This is a high-impact, high-visibility role working at the intersection of AI infrastructure, enterprise software, and developer experience. Responsibilities: Design, develop and maintain databases, system APIs, system integrations, machine learning pipelines and web user interfaces. Scale algorithms designed by data scientists for deployment in high-performance environments. Develop and maintain continuous integration pipelines to deploy the systems. Design and implement scalable backend systems using Golang, C++, Go,Python. Model and manage data using relational (e.g., PostgreSQL , MySQL). Build frontend components and interfaces using TypeScript, and JavaScript when needed. Participate in system architecture discussions and contribute to design decisions. Write clean, idiomatic, and well-documented Go code following best practices and design patterns. Ensure high code quality through unit testing, automation, code reviews, and documentation Communicate technical concepts clearly to both technical and non-technical stakeholders. Qualifications and Criteria: 5–10 years of professional software engineering experience building enterprise-grade platforms. Deep proficiency in Golang , with real-world experience building production-grade systems. Solid knowledge of software architecture, design patterns, and clean code principles. Experience in high-level system design and building distributed systems. Expertise in Python and backend development with experience in PostgreSQL or similar databases. Hands-on experience with unit testing, integration testing, and TDD in Go. Strong debugging, profiling, and performance optimization skills. Excellent communication and collaboration skills. Hands-on experience with frontend development using JavaScript, TypeScript , and HTML/CSS. Bachelor's degree or equivalent experience in a quantitative field (Computer Science, Statistics, Applied Mathematics, Engineering, etc.). Skills: Understanding of optimisation, predictive modelling, machine learning, clustering and classification techniques, and algorithms. Fluency in a programming language (e.g. C++, Go, Python, JavaScript, TypeScript, SQL). Docker, Kubernetes, and Linux knowledge are an advantage. Experience using Git. Knowledge of continuous integration (e.g. Gitlab/Github). Basic familiarity with relational databases, preferably PostgreSQL. Strong grounding in applied mathematics. A firm understanding of and experience with the engineering approach. Ability to interact with other team members via code and design documents. Ability to work on multiple tasks simultaneously. Ability to work in high-pressure environments and meet deadlines. Compensation: Commensurate with experience Position Type: Full-time ( In House ) Location: Ahmedabad / Jamnagar Gujarat India. Submission Requirements CV All academic transcripts Submit to chintanit22@gmail.com , dipakberait@gmail.com with the name of the position you wish to apply for in the subject line. Job Type: Full-time Pay: From ₹40,000.00 per month Benefits: Paid sick time Location Type: In-person Schedule: Day shift Monday to Friday Experience: Full-stack development: 5 years (Preferred) Work Location: In person Speak with the employer +91 9904075544

Work Schedule Standard (Mon-Fri) Environmental Conditions Office Thermo Fisher Scientific Inc. is the world leader in serving science, with an annual revenue of approximately $40 billion. Our Mission is to enable our customers to make the world healthier, cleaner and safer. Whether our customers are accelerating life sciences research, solving sophisticated analytical challenges, growing productivity in their laboratories, improving patient health through diagnostics or the development and manufacture of life-changing therapies, we are here to support them. Our distributed team of more than 130,000 colleagues delivers an unrivalled combination of innovative technologies, purchasing convenience and pharmaceutical services through our industry-leading brands, including Thermo Scientific, Applied Biosystems, Invitrogen, Fisher Scientific, Unity Lab Services, Patheon and PPD. For more information, please visit www.thermofisher.com. About The Role We are seeking a versatile and highly skilled Software Development Engineer with 2–8 years of hands-on experience across systems programming, cloud-native development, and microservices architecture. This is a great opportunity to work on ground breaking systems involving AI/ML model serving & retraining (e.g., NVIDIA Triton), high-performance computing, and distributed services. You will be responsible for crafting, developing, deploying, and maintaining robust software solutions that talk to hardware, cloud infrastructure, and services running at scale. Key Responsibilities Craft and develop scalable and high-performance applications and services using C++, Python and C#. Integrate and optimize model inference using NVIDIA Triton Inference Server. Develop and manage microservices using gRPC and REST APIs for Kubernetes environments. Implement infrastructure as code and deployment pipelines using Docker, Helm, and CI/CD tools. Work closely with hardware systems like Nvidia Jetson/Orin running Linux to diagnose, solve, and optimize hardware-software interactions. Collaborate with multi-functional teams to define system architecture and deliver end-to-end solutions. Write clean, maintainable, and well-tested code following standard methodologies. Continuously monitor and improve system performance, reliability, and scalability. Required Skills And Qualifications 2–8 years of experience in software development using C++, Python, C# languages. Hands-on experience with Triton Inference Server or similar model-serving frameworks, MLFlow. Strong background in cloud-native architectures using AWS, Docker, Kubernetes, and Helm. Strong in Systems Engineering, Linux networking, security, NVIDIA Jetson Infrastructure tooling around OS layer. Experience developing and deploying microservices, particularly with gRPC. Proven understanding of CI/CD pipelines and DevOps standard methodologies. Comfortable working in Linux-based environments and interfacing with hardware components. Strong debugging, performance tuning, and hardware fixing skills. Experience with smart embedded systems or IoT devices. Familiarity with cloud monitoring and observability tools. Understanding of GPU acceleration or edge computing scenarios. Contributions to open-source or involvement in ML/AI system development.

QA Tester – Machine Learning Experience: 1–2 Years Location: Netaji Subhash Place, Delhi Employment Type: Full-time Job Summary: We are looking for a passionate and detail-oriented QA Tester with 1–2 years of experience to join our AI team. In this role, you will work closely with AI-ML engineers and software developers to ensure the quality and reliability of ML models, data pipelines, and model-integrated applications. Key Responsibilities: Design, develop, and execute test plans and test cases for ML models and data pipelines. Validate model outputs against ground truth datasets, with a focus on evaluating classification performance metrics like accuracy, precision, recall, F1-score, and ROC-AUC. Perform functional, regression, and integration testing for applications incorporating ML models. Collaborate with ML engineers to ensure testability and performance of models. Write scripts to automate model testing and data validation. Identify, record, document, and track bugs and model anomalies. Ensure data quality and consistency in training and inference pipelines. Test and validate APIs serving ML models in production. Contribute to continuous improvement of QA processes and tools. Required Skills & Qualifications: Bachelor’s degree in Computer Science, Engineering, or a related field. 1–2 years of experience in QA/testing roles, preferably in ML or data-heavy environments. Solid understanding of QA methodologies, tools, and processes. Experience in testing REST APIs and working with tools like Postman or Swagger. Basic knowledge of Python, with experience in test automation using PyTest or similar frameworks. Familiarity with ML concepts and Docker. Hands-on experience working with structured/unstructured datasets. Ability to write clear, concise, and comprehensive test cases and test reports. Preferred Qualifications: Experience with ML libraries like scikit-learn, TensorFlow, or PyTorch. Exposure to data annotation, labeling, or synthetic data generation tools. Familiarity with version control systems (e.g., Git) and CI/CD workflows. Knowledge of SQL or MongoDB for data validation. Understanding of data drift, model degradation, and ML lifecycle monitoring. Why Join Us? Work on real-world ML products with a measurable impact. Collaborate with a dynamic and skilled team. Opportunity to grow in both QA and ML domains. Flexible work environment and supportive culture. Job Type: Full-time Pay: ₹20,000.00 - ₹30,000.00 per month Benefits: Health insurance Provident Fund Work Location: In person Speak with the employer +91 8178295650

Work From Office What We Offer: Canteen Subsidy Night Shift allowance as per process Health Insurance Tuition Reimbursement Work-Life Balance Initiatives Rewards & Recognition What You’ll Be Doing: User administration (setup and maintaining account) and Maintaining system Verify that peripherals are working properly Quickly arrange repair for hardware in occasion of hardware failure Monitor system performance and create file systems Install software and create a backup and recovery policy Monitor network communication Update system as soon as new version of OS and application software comes out Implement the policies for the use of the computer system and network Setup security policies for users. A system admin must have a strong grasp of computer security (e.g. firewalls and intrusion detection systems). Create new users, resetting user passwords and lock/unlock user accounts Monitor server security & special services etc. DGSET, UPS, Telco systems and CCTV maintenance What We Expect You To Have: 1+ years of exerience working as a System administrator or in a relevant role. Experience of operating systems such as Windows 2000, 2008, NT, XP; Windows 2007 Software programs such as VNS, NT, MS Office Suite, RDP related software, networking; & basic computer hardware Microsoft Network Architecture, DNS, DHCP, WINS, Server Administration Ability to: Re-image workstations as needed for program changes and system updates. Communicate and work well with peers across departments; and prioritize work Language Skills – Ability to read, analyse, and interpret common scientific and technical journals, financial reports, and legal documents. Mathematical Skills – Ability to work with mathematical concepts such as probability and statistical inference, and fundamentals of plane and solid geometry and trigonometry. Ability to apply concepts such as fractions, percentages, ratios, and proportions to practical situations Reasoning Ability – Ability to define problems, collects data, establish facts, and draw valid conclusions Certifications, License & Registrations – MCSE, MCP, related certificate requirement with good Hardware knowledge Physical Demands – The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions Bachelor’s degree from four-year College or University; or 3 years related experience Job Title : System Administrator Location : Gandhinagar Schedule & Shift : US Shift (Rotational)

QA Tester – Machine Learning Experience: 1–2 Years Location: Netaji Subhash Place, Delhi Employment Type: Full-time Job Summary: We are looking for a passionate and detail-oriented QA Tester with 1–2 years of experience to join our AI team. In this role, you will work closely with AI-ML engineers and software developers to ensure the quality and reliability of ML models, data pipelines, and model-integrated applications. Key Responsibilities: Design, develop, and execute test plans and test cases for ML models and data pipelines. Validate model outputs against ground truth datasets, with a focus on evaluating classification performance metrics like accuracy, precision, recall, F1-score, and ROC-AUC. Perform functional, regression, and integration testing for applications incorporating ML models. Collaborate with ML engineers to ensure testability and performance of models. Write scripts to automate model testing and data validation. Identify, record, document, and track bugs and model anomalies. Ensure data quality and consistency in training and inference pipelines. Test and validate APIs serving ML models in production. Contribute to continuous improvement of QA processes and tools. Required Skills & Qualifications: Bachelor’s degree in Computer Science, Engineering, or a related field. 1–2 years of experience in QA/testing roles, preferably in ML or data-heavy environments. Solid understanding of QA methodologies, tools, and processes. Experience in testing REST APIs and working with tools like Postman or Swagger. Basic knowledge of Python, with experience in test automation using PyTest or similar frameworks. Familiarity with ML concepts and Docker. Hands-on experience working with structured/unstructured datasets. Ability to write clear, concise, and comprehensive test cases and test reports. Preferred Qualifications: Experience with ML libraries like scikit-learn, TensorFlow, or PyTorch. Exposure to data annotation, labeling, or synthetic data generation tools. Familiarity with version control systems (e.g., Git) and CI/CD workflows. Knowledge of SQL or MongoDB for data validation. Understanding of data drift, model degradation, and ML lifecycle monitoring. Why Join Us? Work on real-world ML products with a measurable impact. Collaborate with a dynamic and skilled team. Opportunity to grow in both QA and ML domains. Flexible work environment and supportive culture. Job Type: Full-time Pay: ₹20,000.00 - ₹30,000.00 per month Benefits: Health insurance Provident Fund Work Location: In person Speak with the employer +91 8178295650

WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences - the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_ The Role As a Wired System Architect, you will be responsible for participating in standards bodies and understanding wired comms technology trends, defining products (silicon, IP, boards), defining system reference designs & implementation, system architecture engagement with customers, ecosystem partner engagements for solution development, and sales & field enablement for AMD technology adoption. This role requires prior experience in system architecture, systems engineering, design & implementation, test & validation, performance benchmarking preferably at leading OEMs for comms infrastructure segments such as packet/ optical networks, security - data & control path, datacenter interconnect, enterprise/ service provider broadband access, and emerging AI ML model inference applications in wired networks. The Person The ideal person has outstanding problem-solving skills, analytical skills, attention to design details, creative & out of box thinking, interpersonal skills at driving collaboration across cross-functional teams for common goals, penchant for listening to/ learning from peers, persistence & perseverance at the face of obstacles, patience to iterate for optimal solution, and ability to document & share best design practices. AMD culture of execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives is critical for success in this role. Key Responsibilities Specify product roadmaps for FPGA/SoC, IP, custom ASIC aligned with technological trends and emerging use cases Identify customer system requirements, develop system architecture proposals to help customer differentiate, lower cost, power, and TTM Contributing to business strategy & successful execution of strategy to fruition, sales and field training/ enablement and demand generation Identify Define system design requirements, design & implementation of system reference designs Guide/ mobilize/ and work with internal engineering teams and partner ecosystem for timely execution of IP and system reference designs Collaborate with Silicon and Tools marketing teams for alignment and execution on product/ market requirements Enable sales and field to drive AMD technology adoption for successful execution on business, revenue, and profitability goals Preferred Experience 15+ years of experience in design and development of wired subsystems at leading OEM vendors using FPGA/ SoC and/ or ASICs Deep knowledge of Ethernet protocols and associated security standards, packet/ optical networks, and broadband access technologies Expert levels skills in RTL design, FPGA tools and/or ASIC design methodologies Experience in wired subsystem design performance benchmarking, power optimization, and system thermal design considerations Ability to operate effectively in a fast-paced environment with changing deadlines Strong project management, process management, analytical and consulting skills Academic Credentials Bachelor’s in engineering is a must. Master’s or PhD degree is a plus Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.

Job Type: Contractual - Full-time (3-5 months) - Very high chances to a full-time transition. Location: Remote About us: At Kan’s Technologies Global, our mission is to develop the most advanced solutions, products, and platforms that drive business growth, solve real-world challenges, and catalyze innovation across industries worldwide. We specialize in building custom AI/NLP/ML solutions, including Conversational AI, Predictive Analytics, Demand Forecasting, and more empowering organizations to stay ahead in an increasingly digital world. What fuels us? Innovation and Value Creation Role Summary: We are seeking a dynamic and experienced Project Manager with a strong background in managing cross-functional technology teams within the healthcare domain. The ideal candidate will be responsible for overseeing the end-to-end planning, execution, and delivery of healthcare IT projects. This role involves leading a team comprising UI/UX designers, Machine Learning engineers, and Fullstack + Backend developers to ensure timely delivery, quality assurance, and alignment with client and organizational goals. The candidate should bring a structured and proactive approach, leveraging modern project management tools and healthcare domain knowledge to drive success. Roles & Responsibilities: Collaborate with product and engineering teams to identify, extract, and engineer relevant features from diverse datasets to enhance model performance. Research and recommend appropriate machine learning algorithms and statistical techniques for prediction, classification, and optimization tasks within the healthcare domain. Deploy trained models as scalable, low-latency inference endpoints using Azure Machine Learning. Work with DevOps to establish robust MLOps practices for model versioning, monitoring, and continuous retraining. Work closely with Full-Stack and DevOps Engineers to ensure efficient data ingestion from various sources into Azure databases. Perform exploratory data analysis (EDA) to uncover insights, identify trends, and understand data quality. Present findings and model performance clearly to technical and non-technical stakeholders. Monitor the performance and drift of deployed models, ensuring their continued accuracy and relevance. Recommend and implement strategies for model retraining and improvement. Actively contribute to the rapid development and iteration of the MVP, ensuring the ML components are robust, performant, and deliver tangible value. Maintain clear and comprehensive documentation for models, data pipelines, and algorithms. Mandatory Qualifications: Bachelor's degree in Computer Science, IT, Engineering, Healthcare Informatics, or related field Minimum 10 years of project management experience At least 3 years of experience in healthcare or healthtech domain Experience managing cross-functional tech teams (UI/UX, ML, Fullstack + Backend) Proficiency in Agile/Scrum methodologies Hands-on with Jira, Confluence, Slack, Trello/ClickUp, Figma, GitHub/GitLab, Google Workspace Strong communication skills (written and verbal) Strong documentation and reporting skills Preferred Qualifications: PMP, PRINCE2, or Scrum Master (CSM) certification Knowledge of HIPAA, HL7, FHIR, or GDPR in healthcare Basic technical understanding of APIs, ML models, UI/UX workflows, and DevOps, Microsoft Azure Experience in delivering healthcare IT projects (EHR/EMR, patient platforms) Direct client-facing experience in tech project delivery Comfortable managing teams across different time zones What you'll gain: Opportunity to work with international clients and real-world industry problems. Collaborative environment with a team focused on innovation and impact. Performance-based incentives and career growth opportunities. Flexible work structure (remote-first culture). Note: (Compensation Range: upto 13 Lakhs INR per annum), based on experience. At Kan's Technologies Global, we are committed to fostering a diverse and inclusive environment, where everyone is treated with respect and given equal opportunities, regardless of race, gender, religion, or any other characteristic. Discrimination of any kind is not tolerated, and we strive to create a workplace where all individuals can thrive.

Title: - AI Engineer Location: Remote Type: Full-time Experience: 2–5 years About Omelo Omelo is India’s first intelligent pet health companion, an AI-powered assistant that helps pet parents care for their pets proactively. From image-based symptom scanning (skin, eyes, stool) to multilingual chat and vet-backed guidance, we’re building the health stack pets deserve. Every year, millions of pets in India go undiagnosed due to a lack of access or awareness. At Omelo, we’re changing that, with inclusive, AI-first tools accessible via WhatsApp, web, and mobile. Why This Role Matters AI isn’t a support function here; it is the product. From visual health scans to symptom conversations, every user interaction is powered by real-time AI. What You’ll Work On Build and scale computer vision models to detect pet health symptoms (e.g., rashes, eye infections, stool quality) Enhance our multimodal AI assistant, combining vision, NLP, and structured inputs Lead end-to-end AI workflows: data labeling, training, optimization, and deployment Tune models with real-world feedback loops, improving performance across diverse pet types and conditions Collaborate with product, design, and vet advisors to ship features that are clinically useful and intuitive What Success Looks Like In 3–6 Months Ship 2 high-impact CV modules (e.g., skin or stool detection) used in production Improve top-line model precision/recall by 30% via iteration and feedback Deploy your models into production across mobile/web with real user traction Contribute meaningfully to our core health scoring and assistant logic What We’re Looking For 2–5 years of experience building and shipping ML models, especially in health, agri, food, or diagnostic tech Strong hands-on experience with computer vision (CNNs, classification, segmentation, etc.) Comfort with NLP or LLMs for enhancing chat-based UX (Hugging Face, LangChain, etc.) Fluent in Python and familiar with tools like TensorFlow/PyTorch, FastAPI, GCP/AWS Bonus: Experience with mobile inference (ONNX, Core ML, TensorFlow Lite) Bonus: You’ve worked with real-world health or animal datasets (not just academic ones) Tools & Workflow We Work With Python, PyTorch, TensorFlow, Hugging Face FastAPI, Label Studio, ONNX GCP, Firebase, Postgres You don’t need to know them all, but familiarity helps! What We Offer AI is the product, not a side project Real-world pet health data, with vet-labeled image and symptom datasets Direct collaboration with the founder, engineers, and vet experts Fast cycles, zero bureaucracy, and full model ownership Path to early equity and technical leadership for the right person Skills: machine learning,multimodal ai,nlp,datasets,python,mobile,models,ai,data,bonus,building,pytorch,aws,fastapi,tensorflow,computer vision,chat,gcp,health

Description Key Responsibilities: Investigates product problems, understands causal mechanisms, recommends appropriate action, owns problem resolution and documents results with guidance from more experienced team members. Main focus will include working in business processes of Product Preceding Technology (PPT), Value Package Introduction (VPI) or Current Product Support (CPS) and executing technical processes such as Engineering Standard Work (ESW), iDFMEA, Failure Incident Review Group (FIRG) while using tools such as 7-step problem solving, design review checklist and other specialized tools required to support the processes and enable high quality decision making. Obtains input from stakeholders such as technical managers, project leaders, other product and manufacturing engineers and supplier partners to deliver information and recommendations that lead to quality product decisions. Applies academic knowledge and existing experience to take action and make decisions that progress projects forward without sacrificing project quality expectations. Examples of these decisions include day to day project details, analysis or test work instruction details, coordination across discipline areas that are necessary to make quality progress. Owns problem resolution for moderately complex components, products, systems, subsystems or services with technical complexity and ambiguity increasing as experience is gained in the role. Provides independent execution of established work processes and systems, while still developing technology or product knowledge; engages with the improvement of systems and processes. Involves minimal direct management of people, but could involve the coordination and direction of work amongst technicians and/or temporary student employees. Contributes effectively toward team goals, exhibits influence within a work group and continues to develop proficiency in the competency areas critical to success in the role. Responsibilities Competencies: Applies Principles of Statistical Methods - Analyzes technical data using descriptive statistics, probability distributions, graphical analysis, and statistical inference (population and sample, confidence intervals, and hypothesis testing); models relationships between response and independent variables using analysis of variance, regression, and design of experiments to make rigorous, data-based decisions. Cross-Functional Design Integration - Translates the value package requirements that include the voices of many stakeholders into virtual designs, and communicates the capability of the design through an approved cross-functional design review. Design and Application of Open/Closed Loop Controls - Specifies software features that interact with mechanical, hydraulic, chemical and electronic systems to deliver desired system states; specifies control system architectures which include appropriate measurements, correct actuation, and algorithms for Cummins' products; configures and/or understands open/closed loop feedback controls features and the system interactions between hardware and software in Cummins' products. Mechanical Design of Mechanical Systems - Acquires and applies an in-depth understanding of mechanical systems through working knowledge that guides a designer’s ability to create innovative and sound design concepts to meet Cummins and customer expectations; designs for requirements of all lifecycle stages by considering the customer requirements in different operating environments to ensure a robust system. Mechanical Design Specification - Creates complete specifications in the form of solid models, configured engineering bill of materials and detailed drawings that cross-functionally communicate the information required to manufacture and inspect a product per its design intent; considers national, international, industry, and Cummins’ standards that accurately and concisely define the part specification. Product Configuration and Change Management - Establishes a baseline of identified product artifacts to be placed under configuration management; releases, tracks, controls and communicates changes from concept to obsolescence often through work requests; establishes and maintains the integrity of the product artifact baselines. Product Development Execution, Monitoring and Control - Plans, schedules, coordinates and executes the activities involved in developing a product to a respectively aligned hierarchy of requirements and technical profiles; monitors and communicates across functional boundaries to meet project resource and quality expectations; ensures product capability meets or exceeds expectations and takes mitigating actions when project risks are higher than expected; understands the full product life cycle process and stakeholders. Product Failure Mode Avoidance - Mitigates potential product failure modes, by identifying interfaces, functions, functional requirements, interactions, control factors, noise factors, and prioritized potential failure modes and potential failure causes for the system of interest to effectively and efficiently improve the reliability of Cummins’ products. Product Function Modeling, Simulation and Analysis - Impacts product design decisions through the utilization and/or interpretation of computational tools and methods that predict the capability of a product's function relative to its system, sub-system and/or component level requirements. Product Interface Management and Integration - Identifies and analyzes the interfaces and interactions across system boundaries by specifying the requirements and limits to ensure that the product meets requirements; controls the interactions across the system element boundaries by making sure that they remain within specified limits; integrates system elements by creating an integration plan, including identification of method and timing for each activity to make it easier to find, isolate, diagnose, and correct. Product Problem Solving - Solves product problems using a process that protects the customer; determines the assignable cause; implements robust, data-based solutions; and identifies the systemic root causes and recommended actions to prevent problem reoccurrence. Product Verification and Validation Management - Develops product systems validation plans from a variety of inputs to identify failure modes, while managing product risk and relative priority; negotiates product requirements against capability to guide project scope; evaluates analytical, simulation and physical test results to verify product capability and validate requirements; assesses legacy versus proposed system solution capabilities and produces recommendations with technical documentation to support product decisions. System Requirements Engineering - Uses appropriate methods and tools to translate stakeholder needs into verifiable requirements to which designs are developed; establishes acceptance criteria for the system of interest through analysis, allocation and negotiation; tracks the status of requirements throughout the system lifecycle; assesses the impact of changes to system requirements on project scope, schedule, and resources; creates and maintains information linkages to related artifacts. Systems Thinking - Defines the system of interest by drawing the boundaries, identifying its context within its environment, its interfaces, and that it has a lifecycle to aid in planning the problem statement, scope and deliverables ; analyzes linkages and interactions between elements that comprise the system of interest by using appropriate methods, models and integration of outcomes to understand the system, predict its behavior and devise modifications to it in order to produce the desired effects. Technical Documentation - Documents information based on knowledge gained as part of technical function activities; communicates to stakeholders with the goal of enabling improved technical productivity and effective knowledge transfer to others who were not originally part of the initial learning. Collaborates - Building partnerships and working collaboratively with others to meet shared objectives. Communicates effectively - Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences. Decision quality - Making good and timely decisions that keep the organization moving forward. Drives results - Consistently achieving results, even under tough circumstances. Self-development - Actively seeking new ways to grow and be challenged using both formal and informal development channels. Values differences - Recognizing the value that different perspectives and cultures bring to an organization. Education, Licenses, Certifications College, university, or equivalent Bachelor's degree in Engineering or appropriate STEM field is required. Post-graduate (Master's) degree relevant to this discipline area may be required for select roles. This position may require licensing for compliance with export controls or sanctions regulations. Experience Entry level/Early career professional. Preferred candidates would have relevant experience working in either a temporary student employment environment (intern, co-op, or other extracurricular team activities) or as an early career professional in a relevant technical discipline area. Knowledge of MS Office tools is also preferred Qualifications Diploma or bachelor's degree in electrical or Electronics Engineering. Must have experience working with electrical rotating machines in electromagnetic design and development Knowledge of IEC/IS standards is essential. Preferred: Familiarity with high-voltage electrical products. Experience working with cross-functional teams is required. 1 ~ 2 Years of working experience in engineering Independently manage design/VPC projects

We are seeking a highly skilled and self-driven Site Reliability Engineer to join our dynamic team. This role is ideal for someone with a strong foundation in Kubernetes, DevOps, and observability who can also support machine learning infrastructure, GPU optimization, and Big Data ecosystems. You will play a pivotal role in ensuring the reliability, scalability, and performance of our production systems, while also enabling innovation across ML and data teams. Key Responsibilities Automation & Reliability Design, build, and maintain Kubernetes clusters across hybrid or cloud environments (e.g., EKS, GKE, AKS). Implement and optimize CI/CD pipelines using tools like Jenkins, ArgoCD, and GitHub Actions. Develop and maintain Infrastructure as Code (IaC) using Ansible, Terraform, or & Observability : Deploy and maintain monitoring, logging, and tracing tools (e.g., Thanos, Prometheus, Grafana, Loki, Jaeger). Establish proactive alerting and observability practices to identify and address issues before they impact users. ML Ops & GPU Optimization Support and scale ML workflows using tools like Kubeflow, MLflow, and TensorFlow Serving. Work with data scientists to ensure efficient use of GPU resources, optimizing training and inference & Incident Management : Lead root cause analysis for infrastructure and application-level incidents. Participate in the on-call rotation and improve incident response & Automation : Automate operational tasks and service deployment using Python, Shell, Groovy, or Ansible. Write reusable scripts and tools to improve team productivity and reduce manual Learning & Collaboration : Stay up-to-date with emerging technologies in SRE, ML Ops, and observability. Collaborate with cross-functional teams including engineering, data science, and security to ensure system integrity and : 3+ years of experience as an SRE, DevOps Engineer, or equivalent role. Strong experience with Kubernetes ecosystem and container orchestration. Proficiency in DevOps tooling including Jenkins, ArgoCD, and GitOps workflows. Deep understanding of observability tools, with hands-on experience using Thanos and Prometheus stack. Experience with ML platforms (MLflow, Kubeflow) and supporting GPU workloads. Strong scripting skills in Python, Shell, Ansible, or : CKS (Certified Kubernetes Security Specialist) certification. Exposure to Big Data platforms (e.g., Spark, Kafka, Hadoop). Experience with cloud-native environments (AWS, GCP, or Azure). Background in infrastructure security and compliance. (ref:hirist.tech)

Job Summary We are looking for a highly skilled and motivated Full Stack Developer with strong expertise in Python, React.js, and SQL, to join our fast-paced development team. The ideal candidate will have experience building scalable web applications and a strong interest or background in AI/ML-driven applications. You will play a crucial role in delivering intelligent solutions for enterprise clients and top-tier consulting Skills & Experience : Strong Python development skills with experience in Django, Flask, or FastAPI. React.js, Redux, and front-end technologies (JavaScript, HTML5, CSS3). Solid SQL skills with databases like PostgreSQL, MySQL, or MS SQL Server. Experience working with RESTful APIs, JSON, and asynchronous programming. Understanding of version control systems (preferably Git). Experience in writing unit and integration tests. Familiarity with Agile development and DevOps culture. Strong problem-solving skills, ownership mindset, and collaborative / Bonus Skills : Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Knowledge of data pipelines, model inference, and model deployment strategies. Hands-on with cloud platforms like AWS, Azure, or GCP. Familiarity with containerization (Docker) and orchestration (Kubernetes). Exposure to CI/CD pipelines and automated deployment tools. Prior experience in consulting environments or delivering solutions for enterprise Responsibilities : Design, develop, and maintain robust, scalable web applications using Python Build responsive and intuitive frontends using React.js and modern JavaScript frameworks. Collaborate with cross-functional teams including data scientists, designers, and consultants to integrate AI/ML models into applications. Optimize front-end and back-end components for performance, scalability, and maintainability. Build RESTful APIs and integrate with third-party APIs and data services. Contribute to architecture discussions, participate in code reviews, and maintain code quality. Support AI/ML model deployment workflows and data pipeline integration. Keep up with emerging technologies, especially in AI/ML, cloud computing, and web development. Experience of using AI Tools for efficiency gain in : Bachelors degree in Computer Science, Engineering, or a related technical discipline (or equivalent practical experience). (ref:hirist.tech)

Job Description NIQ is looking for a Software Engineer to join our AI ML Engineering team. At NIQ, the Retail Measurement System (RMS) is a powerful analytics service that tracks product sales and market performance across a wide range of retail channels. It provides comprehensive, store-level data that helps businesses understand how their products are performing in the market, benchmark against competitors, and identify growth opportunities. Charlink and Jarvis models are used to predict product placements to its ideal hierarchy product tree. Learn more on the data driven approach to train models efficiently to predict placements based on Characteristics. Developing frontend applications to interact with ML models, integrating inference codes, and providing tools and patterns for enhancing our MLOps cycle. The ideal candidate has strong software design and programming experience, with some expertise in cloud computing, and big data technologies, and strong communication and management skills. You will be part of a diverse, flexible, and collaborative environment where you will be able to apply and develop your skills and knowledge working with unique data and exciting applications. Our Software Engineering platform is based in AngularJS, Java, React, Spring Boot, Typescript, Javascript, Sql and Snowflake, and we continue to adopt the best of breed in cloud-native, low-latency technologies. Who we are looking for: You have a strong entrepreneurial spirit and a thirst to solve difficult challenges through innovation and creativity with a strong focus on results You have a passion for data and the insights it can deliver You are intellectually curious with a broad range of interests and hobbies You take ownership of your deliverables You have excellent analytical communication and interpersonal skills You have excellent communication skills with both technical and non-technical audiences You can work with distributed teams situated globally in different geographies You want to work in a small team with a start-up mentality You can work well under pressure, prioritize work and be well organized. Relish tackling new challenges, paying attention to details, and, ultimately, growing professionally. Responsibilities Design, develop, and maintain scalable web applications using AngularJS for the front end and Java (Spring Boot) for the backend Collaborate closely with cross-functional teams to translate business requirements into technical solutions Optimize application performance, usability, and responsiveness Conduct code reviews, write unit tests, and ensure adherence to coding standards Troubleshoot and resolve software defects and production issues Contribute to architecture and technical documentation Qualifications 5 years of experience as a full stack developer Proficient in AngularJS(Version 12+), Typescript, Java, Spring Framework (especially Spring Boot) Experience with RESTful APIs and microservices architecture Solid understanding of HTML, CSS, JavaScript, and responsive web design Familiarity with relational databases (e.g., MySQL, PostgreSQL) Hands-on experience with version control systems (e.g., GitHub) and CI/CD tools Strong problem-solving abilities and attention to detail 3 - 5+ years of relevant software engineering experience Minimum B.S. degree in Computer Science, Computer Engineering, Information Technology or related field Additional Information Enjoy a flexible and rewarding work environment with peer-to-peer recognition platforms Recharge and revitalize with help of wellness plans made for you and your family Plan your future with financial wellness tools Stay relevant and upskill yourself with career development opportunities Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: https://nielseniq.com/global/en/news-center/diversity-inclusion

Job Title: AI/ML Engineer Location: Hyderabad, India Work Mode: Onsite (5 days/week) Experience: 3+ Years (including 2+ years in AI/ML) Employment Type: Full-time (Onsite | F2F interview mandatory) Position Overview: We are looking for a highly motivated and skilled AI/ML Engineer to join our team in Hyderabad . This is a full-time, onsite role offering the opportunity to build and deploy real-world AI applications using cutting-edge tools, including AWS Bedrock , SageMaker , and other cloud-native services. The ideal candidate will have a passion for solving business problems with AI and experience bringing AI models to life in production environments. Key Responsibilities: Design, build, and deploy end-to-end AI/ML solutions for real-world applications Work with AWS services like Bedrock , SageMaker , Lambda , and Step Functions for model training, inference, and orchestration Collaborate with product, engineering, and data teams to define technical solutions Conduct data preparation, feature engineering, model training, and performance tuning Ensure scalable and cost-effective AI model deployment in cloud environments Stay current on emerging trends in Generative AI, foundation models, and MLOps practices Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field 3+ years of total experience in software development, with 2+ years focused on AI/ML Proven experience in building and deploying AI applications in production Hands-on expertise with Python and ML frameworks like PyTorch , TensorFlow , or Scikit-learn Experience with AWS AI/ML tools, especially SageMaker and Bedrock Solid understanding of data pipelines, APIs, and inference optimization Familiarity with prompt engineering and using foundation models in enterprise applications Preferred Skills: Exposure to LLMs , RAG architectures , or agentic AI systems Understanding of MLOps principles and tools (CI/CD for ML, monitoring, retraining loops) Experience in NLP, computer vision, or time-series forecasting Work Arrangement: Location: Hyderabad (onsite only) Work Schedule: Monday to Friday (5 days a week, in-office)

Job Title: AI/ML Engineer (Python AWS REST APIs) Department: Web Location: Indore Job Type: Full-time Experience: 3-5 years Notice Period: 0-15 days (immediate joiners preferred) Work Arrangement: On-site (Work from Office) Overview Advantal Technologies is seeking a passionate AI/ML Engineer to join our team in building the core AI-driven functionality of an intelligent visual data encryption system. The role involves designing, training, and deploying AI models (e.g., CLIP, DCGANs, Decision Trees), integrating them into a secure backend, and operationalizing the solution via AWS cloud services and Python-based APIs. Key Responsibilities: AI/ML Development Design and train deep learning models for image classification and sensitivity tagging using CLIP, DCGANs, and Decision Trees. Build synthetic datasets using DCGANs for balancing. Fine-tune pre-trained models for customized encryption logic. Implement explainable classification logic for model outputs. Validate model performance using custom metrics and datasets. API Development Design and develop Python RESTful APIs using FastAPI or Flask for: Image upload and classification Model inference endpoints Encryption trigger calls Integrate APIs with AWS Lambda and Amazon API Gateway. AWS Integration Deploy and manage AI models on Amazon SageMaker for training and real-time inference. Use AWS Lambda for serverless backend compute. Store encrypted image data on Amazon S3 and metadata on Amazon RDS (PostgreSQL). Use AWS Cognito for secure user authentication and KMS for key management. Monitor job status via CloudWatch and enable secure, scalable API access. Required Skills & Experience: Must-Have 35 years of experience in AI/ML (especially vision-based systems). Strong experience with PyTorch or TensorFlow for model development. Proficient in Python with experience building RESTful APIs. Hands-on experience with Amazon SageMaker, Lambda, API Gateway, and S3. Knowledge of OpenSSL/PyCryptodome or basic cryptographic concepts. Understanding of model deployment, serialization, and performance tuning. Nice-to-Have Experience with CLIP model fine-tuning. Familiarity with Docker, GitHub Actions, or CI/CD pipelines. Experience in data classification under compliance regimes (e.g., GDPR, HIPAA). Familiarity with multi-tenant SaaS design patterns. Tools & Technologies: Python, PyTorch, TensorFlow FastAPI, Flask AWS: SageMaker, Lambda, S3, RDS, Cognito, API Gateway, KMS Git, Docker, Postgres, OpenCV, OpenSSL If interested, please share your resume to hr@advantal.ne.

Description Key Responsibilities: Investigates product problems, understands causal mechanisms, recommends appropriate action, owns problem resolution and documents results with guidance from more experienced team members. Main focus will include working in business processes of Product Preceding Technology (PPT), Value Package Introduction (VPI) or Current Product Support (CPS) and executing technical processes such as Engineering Standard Work (ESW), iDFMEA, Failure Incident Review Group (FIRG) while using tools such as 7-step problem solving, design review checklist and other specialized tools required to support the processes and enable high quality decision making. Obtains input from stakeholders such as technical managers, project leaders, other product and manufacturing engineers and supplier partners to deliver information and recommendations that lead to quality product decisions. Applies academic knowledge and existing experience to take action and make decisions that progress projects forward without sacrificing project quality expectations. Examples of these decisions include day to day project details, analysis or test work instruction details, coordination across discipline areas that are necessary to make quality progress. Owns problem resolution for moderately complex components, products, systems, subsystems or services with technical complexity and ambiguity increasing as experience is gained in the role. Provides independent execution of established work processes and systems, while still developing technology or product knowledge; engages with the improvement of systems and processes. Involves minimal direct management of people, but could involve the coordination and direction of work amongst technicians and/or temporary student employees. Contributes effectively toward team goals, exhibits influence within a work group and continues to develop proficiency in the competency areas critical to success in the role. Responsibilities Competencies: Applies Principles of Statistical Methods - Analyzes technical data using descriptive statistics, probability distributions, graphical analysis, and statistical inference (population and sample, confidence intervals, and hypothesis testing); models relationships between response and independent variables using analysis of variance, regression, and design of experiments to make rigorous, data-based decisions. Cross-Functional Design Integration - Translates the value package requirements that include the voices of many stakeholders into virtual designs, and communicates the capability of the design through an approved cross-functional design review. Design and Application of Open/Closed Loop Controls - Specifies software features that interact with mechanical, hydraulic, chemical and electronic systems to deliver desired system states; specifies control system architectures which include appropriate measurements, correct actuation, and algorithms for Cummins' products; configures and/or understands open/closed loop feedback controls features and the system interactions between hardware and software in Cummins' products. Mechanical Design of Mechanical Systems - Acquires and applies an in-depth understanding of mechanical systems through working knowledge that guides a designer’s ability to create innovative and sound design concepts to meet Cummins and customer expectations; designs for requirements of all lifecycle stages by considering the customer requirements in different operating environments to ensure a robust system. Mechanical Design Specification - Creates complete specifications in the form of solid models, configured engineering bill of materials and detailed drawings that cross-functionally communicate the information required to manufacture and inspect a product per its design intent; considers national, international, industry, and Cummins’ standards that accurately and concisely define the part specification. Product Configuration and Change Management - Establishes a baseline of identified product artifacts to be placed under configuration management; releases, tracks, controls and communicates changes from concept to obsolescence often through work requests; establishes and maintains the integrity of the product artifact baselines. Product Development Execution, Monitoring and Control - Plans, schedules, coordinates and executes the activities involved in developing a product to a respectively aligned hierarchy of requirements and technical profiles; monitors and communicates across functional boundaries to meet project resource and quality expectations; ensures product capability meets or exceeds expectations and takes mitigating actions when project risks are higher than expected; understands the full product life cycle process and stakeholders. Product Failure Mode Avoidance - Mitigates potential product failure modes, by identifying interfaces, functions, functional requirements, interactions, control factors, noise factors, and prioritized potential failure modes and potential failure causes for the system of interest to effectively and efficiently improve the reliability of Cummins’ products. Product Function Modeling, Simulation and Analysis - Impacts product design decisions through the utilization and/or interpretation of computational tools and methods that predict the capability of a product's function relative to its system, sub-system and/or component level requirements. Product Interface Management and Integration - Identifies and analyzes the interfaces and interactions across system boundaries by specifying the requirements and limits to ensure that the product meets requirements; controls the interactions across the system element boundaries by making sure that they remain within specified limits; integrates system elements by creating an integration plan, including identification of method and timing for each activity to make it easier to find, isolate, diagnose, and correct. Product Problem Solving - Solves product problems using a process that protects the customer; determines the assignable cause; implements robust, data-based solutions; and identifies the systemic root causes and recommended actions to prevent problem reoccurrence. Product Verification and Validation Management - Develops product systems validation plans from a variety of inputs to identify failure modes, while managing product risk and relative priority; negotiates product requirements against capability to guide project scope; evaluates analytical, simulation and physical test results to verify product capability and validate requirements; assesses legacy versus proposed system solution capabilities and produces recommendations with technical documentation to support product decisions. System Requirements Engineering - Uses appropriate methods and tools to translate stakeholder needs into verifiable requirements to which designs are developed; establishes acceptance criteria for the system of interest through analysis, allocation and negotiation; tracks the status of requirements throughout the system lifecycle; assesses the impact of changes to system requirements on project scope, schedule, and resources; creates and maintains information linkages to related artifacts. Systems Thinking - Defines the system of interest by drawing the boundaries, identifying its context within its environment, its interfaces, and that it has a lifecycle to aid in planning the problem statement, scope and deliverables ; analyzes linkages and interactions between elements that comprise the system of interest by using appropriate methods, models and integration of outcomes to understand the system, predict its behavior and devise modifications to it in order to produce the desired effects. Technical Documentation - Documents information based on knowledge gained as part of technical function activities; communicates to stakeholders with the goal of enabling improved technical productivity and effective knowledge transfer to others who were not originally part of the initial learning. Collaborates - Building partnerships and working collaboratively with others to meet shared objectives. Communicates effectively - Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences. Decision quality - Making good and timely decisions that keep the organization moving forward. Drives results - Consistently achieving results, even under tough circumstances. Self-development - Actively seeking new ways to grow and be challenged using both formal and informal development channels. Values differences - Recognizing the value that different perspectives and cultures bring to an organization. Education, Licenses, Certifications College, university, or equivalent Bachelor's degree in Engineering or appropriate STEM field is required. Post-graduate (Master's) degree relevant to this discipline area may be required for select roles. This position may require licensing for compliance with export controls or sanctions regulations. Experience Entry level/Early career professional. Preferred candidates would have relevant experience working in either a temporary student employment environment (intern, co-op, or other extracurricular team activities) or as an early career professional in a relevant technical discipline area. Knowledge of MS Office tools is also preferred Qualifications Job Specific Requirements:- Diploma or bachelor's degree in electrical or Electronics Engineering. Must have experience working with electrical rotating machines in electromagnetic design and development Knowledge of IEC/IS standards is essential. Preferred: Familiarity with high-voltage electrical products. Experience working with cross-functional teams is required. 1 ~ 2 Years of working experience in engineering Independently manage design/VPC projects Job Engineering Organization Cummins Inc. Role Category Hybrid Job Type Exempt - Experienced ReqID 2417484 Relocation Package Yes

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Director Job Description & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us. At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organizations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organizational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organizations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Responsibilities: Strategic Leadership · Define and execute the long-term roadmap for Agentic AI and GenAI initiatives. · Identify and prioritize opportunities where autonomous agents and generative AI can drive business value. · Collaborate with executive leadership to align AI strategy with overall business goals. Technology & Research Oversight · Lead architecture and development of intelligent agent frameworks (e.g., goal-driven, tool-using agents). · Oversee the application of LLMs, multimodal models, and fine-tuning strategies for domain-specific use cases. · Evaluate and integrate emerging GenAI/Agentic technologies (e.g., AutoGPT, LangChain, ReAct, DSPy, etc.). Team Management & Collaboration · Build, mentor, and scale a world-class team of AI researchers, ML engineers, and product managers. · Foster a strong interdisciplinary culture of innovation and experimentation. · Collaborate cross-functionally with data engineering, product, legal, and design teams. Operational Excellence · Oversee data pipelines, model training, inference infrastructure, and model governance. · Establish benchmarks and evaluation protocols for agent behavior, safety, and performance. · Ensure ethical and responsible AI development practices are followed. Mandatory skill sets: GenAI/Agentic technologies (e.g., AutoGPT, LangChain, ReAct, DSPy, etc.). Preferred skill sets: · Lang Experience in industries such as finance, consulting · Track record of publishing or contributing to open-source AI frameworks. · Understanding of regulatory, ethical, and societal implications of autonomous AI system Years of experience required: 14-17 Education qualification: B.Tech / M.Tech / MBA / MCA Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Master of Business Administration, Master of Engineering, Bachelor of Engineering Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Generative AI Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, Analytical Thinking, C++ Programming Language, Coaching and Feedback, Communication, Complex Data Analysis, Creativity, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Embracing Change, Emotional Regulation, Empathy, GPU Programming, Inclusion, Influence, Innovation, Intellectual Curiosity {+ 37 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date

Company Description Quantanite is a business process outsourcing (BPO) and customer experience (CX) solutions company that helps fast-growing companies and leading global brands to transform and grow. We do this through a collaborative and consultative approach, rethinking business processes and ensuring our clients employ the optimal mix of automation and human intelligence. We’re an ambitious team of professionals spread across four continents and looking to disrupt our industry by delivering seamless customer experiences for our clients, backed up with exceptional results. We have big dreams and are constantly looking for new colleagues to join us who share our values, passion, and appreciation for diversity Job Description We are looking for a Python Backend Engineer with exposure to AI engineering to join our team in building a scalable, cognitive data platform. This platform will crawl and process unstructured data sources, enabling intelligent data extraction and analysis. The ideal candidate will have deep expertise in backend development using FastAPI, RESTful APIs, SQL, and Azure data technologies, with a secondary focus on integrating AI/ML capabilities into the product. Core Responsibilities Design and develop high-performance backend services using Python (FastAPI). Develop RESTful APIs to support data ingestion, transformation, and AI-based feature access. Work closely with DevOps and data engineering teams to integrate backend services with Azure data pipelines and databases. Manage database schemas, write complex SQL queries, and support ETL processes using Python-based tools. Build secure, scalable, and production-ready services following best practices in logging, authentication, and observability. Implement background tasks and async event-driven workflows for data crawling and processing. AI Engineering Contributions : Support integration of AI models (NLP, summarization, information retrieval) within backend APIs. Collaborate with AI team to deploy lightweight inference pipelines using PyTorch, TensorFlow, or ONNX. Participate in training data pipeline design and minor model fine-tuning as needed for business logic. Contribute to the testing, logging, and monitoring of AI agent behavior in production environments. Qualifications 3+ years of experience in Python backend development, with strong experience in FastAPI or equivalent frameworks. Solid understanding of RESTful API design, asynchronous programming, and web application architecture. Proficiency in working with relational databases (e.g., PostgreSQL, MS SQL Server) and Azure cloud services. Experience with ETL workflows, job scheduling, and data pipeline orchestration (Airflow, Prefect, etc.). Exposure to machine learning libraries (e.g., Scikit-learn, Transformers, OpenAI APIs) is a plus. Familiarity with containerization (Docker), CI/CD practices, and performance tuning. A mindset of code quality, scalability, documentation, and collaboration. Additional Information Benefits At Quantanite, we ask a lot of our associates, which is why we give so much in return. In addition to your compensation, our perks include: Dress: Wear anything you like to the office. We want you to feel as comfortable as when working from home. Employee Engagement: Experience our family community and embrace our culture where we bring people together to laugh and celebrate our achievements. Professional development: We love giving back and ensure you have opportunities to grow with us and even travel on occasion. Events: Regular team and organisation-wide get-togethers and events. Value orientation: Everything we do at Quantanite is informed by our Purpose and Values. We Build Better. Together. Future development: At Quantanite, you’ll have a personal development plan to help you improve in the areas you’re looking to develop over the coming years. Your manager will dedicate time and resources to supporting you in getting you to the next level. You’ll also have the opportunity to progress internally. As a fast-growing organization, our teams are growing, and you’ll have the chance to take on more responsibility over time. So, if you’re looking for a career full of purpose and potential, we’d love to hear from you!

Description About the Company - We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place. About The Role We’re looking for an experienced Data Scientist who will help us build marketing attribution, causal inference, and uplift models to improve the effectiveness and efficiency of our marketing efforts. This person will also design experiments and help us drive consistent approach to experimentation and campaign measurement to support a range of marketing, customer engagement, and digital use cases. This Lead Data Scientist brings significant experience in designing, developing, and delivering statistical models and AI/ML algorithms for marketing and digital optimization use cases on large-scale data sets in a cloud environment. They show rigor in how they prototype, test, and evaluate algorithm performance both in the testing phase of algorithm development and in managing production algorithms. They demonstrate advanced knowledge of statistical and machine learning techniques along with ensuring the ethical use of data in the algorithm design process. At Salesforce, Trust is our number one value and we expect all applications of statistical and machine learning models to adhere to our values and policies to ensure we balance business needs with responsible uses of technology. Responsibilities As part of the Marketing Effectiveness Data Science team within the Salesforce Marketing Data Science organization, develop statistical and machine learning models to improve marketing effectiveness - e.g., marketing attribution models, causal inference models, uplift models, etc. Develop optimization and simulation algorithms to provide marketing investment and allocation recommendations to improve ROI by optimizing spend across marketing channels. Own the full lifecycle of model development from ideation and data exploration, algorithm design and testing, algorithm development and deployment, to algorithm monitoring and tuning in production. Design experiments to support marketing, customer experience, and digital campaigns and develop statistically sound models to measure impact. Collaborate with other data scientists to develop and operationalize consistent approaches to experimentation and campaign measurement. Be a master in cross-functional collaboration by developing deep relationships with key partners across the company and coordinating with working teams. Constantly learn, have a clear pulse on innovation across the enterprise SaaS, AdTech, paid media, data science, customer data, and analytics communities. Required Skills 8+ years of experience designing models for marketing optimization such as multi-channel attribution models, customer lifetime value models, propensity models, uplift models, etc. using statistical and machine learning techniques. 8+ years of experience using advanced statistical techniques for experiment design (A/B and multi-cell testing) and causal inference methods for understanding business impact. Must have multiple, robust examples of using these techniques to measure effectiveness of marketing efforts and to solve business problems on large-scale data sets. 8+ years of experience with one or more programming languages such as Python, R, PySpark, Java. Expert-level knowledge of SQL with strong data exploration and manipulation skills. Experience using cloud platforms such as GCP and AWS for model development and operationalization is preferred. Must have superb quantitative reasoning and interpretation skills with strong ability to provide analysis-driven business insight and recommendations. Excellent written and verbal communication skills; ability to work well with peers and leaders across data science, marketing, and engineering organizations. Creative problem-solver who simplifies problems to their core elements. B2B customer data experience a big plus. Advanced Salesforce product knowledge is also a plus.

Role Summary 1. Demonstrate solid proficiency in Python development, writing clean, maintainable code. 2. Collaborator in the design and implementation of AI-driven applications leveraging large language models (LLMs). 3. Develop and maintain Django-based RESTful APIs to support backend services. 4. Integrate with LLM provider APIs (e.g., GPT, Claude, Cohere) and agent frameworks (LangChain, AgentStudio). 5. Build and optimize data pipelines for model training and inference using Pandas, NumPy, and Scikit-learn. 6. Ensure robust unit and integration testing via pytest to maintain high code quality. 7. Participate in agile ceremonies, contributing estimations, design discussions, and retrospectives. 8. Troubleshoot, debug, and optimize performance in multi-threaded and distributed environments. 9. Document code, APIs, and data workflows in accordance with software development best practices. 10. Continuously learn and apply new AI/ML tools, frameworks, and cloud services. Key Responsibilities 1. Write, review, and optimize Python code for backend services and data science workflows. 2. Design and implement Django REST APIs, ensuring scalability and security. 3. Integrate LLMs into applications: handle prompt construction, API calls, and result processing. 4. Leverage agent frameworks (LangChain, AgentStudio) to orchestrate complex LLM workflows. 5. Develop and maintain pytest suites covering unit, integration, and end-to-end tests. 6. Build ETL pipelines to preprocess data for model training and feature engineering. 7. Work with relational databases (PostgreSQL) and vector stores (FAISS, Weaviate, Milvus). 8. Containerize applications using Docker and deploy on Kubernetes or serverless platforms (AWS, GCP, Azure). 9. Monitor and troubleshoot application performance, logging, and error handling. 10. Collaborate with data scientists to deploy and serve ML models via FastAPI or vLLM. 11. Maintain CI/CD pipelines for automated testing and deployment. 12. Engage in technical learning sessions and share best practices across the team. Desired Skills & Qualifications - 1–3 years of hands-on experience in Python application development. - Proven pytest expertise, with a focus on test-driven development. - Practical knowledge of Django (or FastAPI) for building RESTful services. - Experience with LLM APIs (OpenAI, Anthropic, Cohere) and prompt engineering. - Familiarity with at least one agent framework (LangChain, AgentStudio). - Working experience in data science libraries: NumPy, Pandas, Scikit-learn. - Exposure to ML model serving tools (MLflow, FastAPI, vLLM). - Experience with container orchestration (Docker, Kubernetes, Docker Swarm). - Basic understanding of cloud platforms (AWS, Azure, or GCP). - Knowledge of SQL and database design; familiarity with vector databases. - Eagerness to learn emerging AI/ML technologies and frameworks. - Excellent problem-solving, debugging, and communication skills. Education & Attitude - Bachelor’s or Master’s in Computer Science, Data Science, Statistics, Mathematics, or related field. - Growth-mindset learner: proactive in upskilling and sharing knowledge. - Strong collaboration ethos and adaptability in a fast-paced AI environment.

Job Description Oracle Cloud Infrastructure (OCI) is a strategic growth area for Oracle. It is a comprehensive cloud service offering in the enterprise software industry, spanning Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). OCI is currently building a future-ready Gen2 cloud Data Science service platform. At the core of this platform, lies Cloud AI Cloud Service. What OCI AI Cloud Services are: A set of services on the public cloud, that are powered by ML and AI to meet the Enterprise modernization needs, and that work out of the box. These services and models can be easily specialized for specific customers/domains by demonstrating existing OCI services. Key Points: Enables customers to add AI capabilities to their Apps and Workflows easily via APIs or Containers, Useable without needing to build AI expertise in-house and Covers key gaps – Decision Support, NLP, for Public Clouds and Enterprise in NLU, NLP, Vision and Conversational AI. You’re Opportunity: As we innovate to provide a single collaborative ML environment for data-science professionals, we will be extremely happy to have you join us and share the very future of our Machine Learning platform - by building an AI Cloud service. We are addressing exciting challenges at the intersection of artificial intelligence and innovative cloud infrastructure. We are building cloud services in Computer vision for Image/Video and Document Analysis, Decision Support (Anomaly Detection, Time series forecasting, Fraud detection, Content moderation, Risk prevention, predictive analytics), Natural Language Processing (NLP), and, Speech that works out of the box for enterprises. Our product vision includes the ability for enterprises to be able to customize the services for their business and train them to specialize in their data by creating micro models that enhance the global AI models. What You’ll Do Develop scalable infrastructure, including microservices and a backend, that automates training, deployment, and optimization of ML model inference. Building a core of Artificial Intelligence and AI services such as Vision, Speech, Language, Decision, and others. Brainstorm and design various POCs using AI Perpetual AI Services for new or existing enterprise problems. Collaborate with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively communicating your needs, understanding theirs, and addressing external and internal shareholder product challenges. Lead research and development efforts to explore new tools, frameworks, and methodologies to improve backend development processes. Experiment with ML models in Python/C++ using machine learning libraries (Pytorch, ONNX, TensorRT, Triton, TensorFlow, Jax), etc. Leverage Cloud technology – Oracle Cloud (OCI), AWS, GCP, Azure, or similar technology. Qualifications Master’s degree or equivalent experience (preferred) in computer science, Statistics or Mathematics, artificial intelligence, machine learning, Computer vision, operations research, or related technical field. 3+ years for PhD or equivalent experience, 5+ years for Masters, or demonstrated ability designing, implementing, and deploying machine learning models in production environments. Practical experience in design, implementation, and production deployment of distributed systems using microservices architecture and APIs using common frameworks like Spring Boot (Java), etc. Practical experience working in a cloud environment: Oracle Cloud (OCI), AWS, GCP, Azure, and containerization (Docker, Kubernetes). Working knowledge of current techniques, approaches, and inference optimization strategies in machine learning models. Experience with performance tuning, scalability, and load balancing techniques. Expert in at least one high-level language such as Java/C++ (Java preferred). Expert in at least one scripting language such as Python, Javascript, and Shell . Deep understanding of data structures, and algorithms, and excellent problem-solving skills. Experience or willingness to learn and work in Agile and iterative development and DevOps processes. Strong drive to learn and master new technologies and techniques. You enjoy a fast-paced work environment. Additional Preferred Qualifications Experience with Cloud Native Frameworks tools and products is a plus Experience in Computer vision tasks like Image Classification, Object Detection, Segmentation, Text detection & recognition, Information extraction from documents, etc. Having an impressive set of GitHub projects or contributions to open-source technologies is a plus Hands-on experience with horizontally scalable data stores such as Hadoop and other NoSQL technologies like Cassandra is a plus. Our vision is to provide an immersive AI experience on Oracle Cloud. Aggressive as it might sound, our growth journey is fueled by highly energetic, technology-savvy engineers like YOU who are looking to grow with us to meet the demands of building a powerful next-generation platform. Are you ready to do something big? Career Level - IC3 About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

About the Role: We are seeking a highly experienced Voice AI /ML Engineer to lead the design and deployment of real-time voice intelligence systems. This role focuses on ASR, TTS, speaker diarization, wake word detection, and building production-grade modular audio processing pipelines to power next-generation contact centre solutions, intelligent voice agents, and telecom-grade audio systems. You will work at the intersection of deep learning, streaming infrastructure, and speech/NLP technology, creating scalable, low-latency systems across diverse audio formats and real-world applications. Key Responsibilities: Voice & Audio Intelligence:  Build, fine-tune, and deploy ASR models (e.g., Whisper, wav2vec2.0, Conformer) for real-time transcription.  Develop and finetune high-quality TTS systems using VITS, Tacotron, FastSpeech for lifelike voice generation and cloning.  Implement speaker diarization for segmenting and identifying speakers in multi-party conversations using embeddings (x-vectors/d-vectors) and clustering (AHC, VBx, spectral clustering).  Design robust wake word detection models with ultra-low latency and high accuracy in noisy conditions. Real-Time Audio Streaming & Voice Agent Infrastructure:  Architect bi-directional real-time audio streaming pipelines using WebSocket, gRPC, Twilio Media Streams, or WebRTC.  Integrate voice AI models into live voice agent solutions, IVR automation, and AI contact center platforms.  Optimize for latency, concurrency, and continuous audio streaming with context buffering and voice activity detection (VAD).  Build scalable microservices to process, decode, encode, and stream audio across common codecs (e.g., PCM, Opus, μ-law, AAC, MP3) and containers (e.g., WAV, MP4). Deep Learning & NLP Architecture:  Utilize transformers, encoder-decoder models, GANs, VAEs, and diffusion models, for speech and language tasks.  Implement end-to-end pipelines including text normalization, G2P mapping, NLP intent extraction, and emotion/prosody control.  Fine-tune pre-trained language models for integration with voice-based user interfaces. Modular System Development:  Build reusable, plug-and-play modules for ASR, TTS, diarization, codecs, streaming inference, and data augmentation.  Design APIs and interfaces for orchestrating voice tasks across multi-stage pipelines with format conversions and buffering.  Develop performance benchmarks and optimize for CPU/GPU, memory footprint, and real-time constraints. Engineering & Deployment:  Writing robust, modular, and efficient Python code  Experience with Docker, Kubernetes, cloud deployment (AWS, Azure, GCP)  Optimize models for real-time inference using ONNX, TorchScript, and CUDA, including quantization, context-aware inference, model caching.  On device voice model deployment. Why join us?  Impactful Work: Play a pivotal role in safeguarding Tanla's assets, data, and reputation in the industry.  Tremendous Growth Opportunities: Be part of a rapidly growing company in the telecom and CPaaS space, with opportunities for professional development.  Innovative Environment: Work alongside a world-class team in a challenging and fun environment, where innovation is celebrated. Tanla is an equal opportunity employer. We champion diversity and are committed to creating an inclusive environment for all employees. www.tanla.com

Senior Software Engineer – Back end and Inferencing– Technology (Maersk) This position will be based in India – Bangalore/Pune A.P. Moller - Maersk A.P. Moller – Maersk is the global leader in container shipping services. The business operates in 130 countries and employs 80,000 staff. An integrated container logistics company, Maersk aims to connect and simplify its customers’ supply chains. Today, we have more than 180 nationalities represented in our workforce across 131 Countries and this mean, we have elevated level of responsibility to continue to build inclusive workforce that is truly representative of our customers and their customers and our vendor partners too. The Brief We are seeking a Senior Software Engineer with deep backend expertise to lead the development of scalable infrastructure for LLM inferencing, Model Context Protocol (MCP) integration, Agent-to-Agent (A2A) communication, prompt engineering, and robust API platforms. This role sits at the core of our AI systems stack — enabling structured, contextual, and intelligent communication between models, agents, and services. You'll design modular backend services that interface seamlessly with inferencing engines, orchestrate model contexts, and expose capabilities via APIs for downstream products and agents. What I'll be doing – your accountabilities? Architect and implement backend services that support dynamic model context management via MCP for LLM-based systems. Build scalable and token-efficient inference pipelines with support for streaming, context merging, memory, and retrieval. Enable Agent-to-Agent (A2A) messaging and task coordination through contextual protocols, message contracts, and execution chains. Design and maintain developer-friendly, secure, and versioned APIs for agents, tools, memory, context providers, and prompt libraries. Lead efforts in prompt engineering workflows including templating, contextual overrides, and programmatic prompt generation. Collaborate across engineering, ML, and product teams to define and implement context-aware agent systems and inter-agent communication standards to enable closed-loop enterprise AI Services ready for consumption by the enterprise. Own end-to-end delivery of infrastructure, inferencing, back-end, API and communication management in multi-agent system. Ensure models are modular, extensible, and easily integrated with external services/platforms (e.g., dashboards, analytics, AI agents). Foundational / Must Have Skills Bachelor’s, Master’s or Phd in Computer Science, Engineering, or related technical field. 8+ years of experience in backend systems design and development — ideally in AI/ML or data infrastructure domains. Strong proficiency in Python (FastAPI preferred); additional experience with Node.js, Go, or Rust is a plus. Experience with LLM inferencing pipelines, context windowing, and chaining prompts with memory/state persistence. Familiarity with or active experience implementing Model Context Protocol (MCP) or similar abstraction layers for context-driven model orchestration. Strong understanding of REST/GraphQL API design, OAuth2/JWT-based auth, and event-driven backend architectures. Practical knowledge of Redis, PostgreSQL, and one or more vector databases (e.g., Weaviate, Qdrant). Comfortable working with containerized applications, CI/CD pipelines, and cloud-native deployments (AWS/GCP/Azure). Preferred To Have Experience building or contributing to agent frameworks (e.g., LangGraph, CrewAI, AutoGen, Agno etc.). Background in multi-agent systems, dialogue orchestration, or synthetic workflows. Familiarity with OpenAI, Anthropic, HuggingFace, or open-weight model APIs and tool-calling protocols. Strong grasp of software security, observability (OpenTelemetry, Prometheus), and system performance optimization. Experience designing abstraction layers for LLM orchestration across different provider APIs (OpenAI, Claude, local inference). What You Can Expect Opportunity to lead backend architecture for cutting-edge, LLM-native systems. High-impact role in shaping the future of context-aware AI agent communication. Autonomy to drive backend standards, protocols, and platform capabilities across the org. Collaborative, remote-friendly culture with deep technical peers. As a performance-oriented company, we strive to always recruit the best person for the job – regardless of gender, age, nationality, sexual orientation or religious beliefs. We are proud of our diversity and see it as a genuine source of strength for building high-performing teams. Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements. We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com.

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Data Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. About the Company - We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place. About the role We’re looking for an experienced Data Scientist who will help us build marketing attribution, causal inference, and uplift models to improve the effectiveness and efficiency of our marketing efforts. This person will also design experiments and help us drive consistent approach to experimentation and campaign measurement to support a range of marketing, customer engagement, and digital use cases. This Lead Data Scientist brings significant experience in designing, developing, and delivering statistical models and AI/ML algorithms for marketing and digital optimization use cases on large-scale data sets in a cloud environment. They show rigor in how they prototype, test, and evaluate algorithm performance both in the testing phase of algorithm development and in managing production algorithms. They demonstrate advanced knowledge of statistical and machine learning techniques along with ensuring the ethical use of data in the algorithm design process. At Salesforce, Trust is our number one value and we expect all applications of statistical and machine learning models to adhere to our values and policies to ensure we balance business needs with responsible uses of technology. Responsibilities As part of the Marketing Effectiveness Data Science team within the Salesforce Marketing Data Science organization, develop statistical and machine learning models to improve marketing effectiveness - e.g., marketing attribution models, causal inference models, uplift models, etc. Develop optimization and simulation algorithms to provide marketing investment and allocation recommendations to improve ROI by optimizing spend across marketing channels. Own the full lifecycle of model development from ideation and data exploration, algorithm design and testing, algorithm development and deployment, to algorithm monitoring and tuning in production. Design experiments to support marketing, customer experience, and digital campaigns and develop statistically sound models to measure impact. Collaborate with other data scientists to develop and operationalize consistent approaches to experimentation and campaign measurement. Be a master in cross-functional collaboration by developing deep relationships with key partners across the company and coordinating with working teams. Constantly learn, have a clear pulse on innovation across the enterprise SaaS, AdTech, paid media, data science, customer data, and analytics communities. Required Skills 8+ years of experience designing models for marketing optimization such as multi-channel attribution models, customer lifetime value models, propensity models, uplift models, etc. using statistical and machine learning techniques. 8+ years of experience using advanced statistical techniques for experiment design (A/B and multi-cell testing) and causal inference methods for understanding business impact. Must have multiple, robust examples of using these techniques to measure effectiveness of marketing efforts and to solve business problems on large-scale data sets. 8+ years of experience with one or more programming languages such as Python, R, PySpark, Java. Expert-level knowledge of SQL with strong data exploration and manipulation skills. Experience using cloud platforms such as GCP and AWS for model development and operationalization is preferred. Must have superb quantitative reasoning and interpretation skills with strong ability to provide analysis-driven business insight and recommendations. Excellent written and verbal communication skills; ability to work well with peers and leaders across data science, marketing, and engineering organizations. Creative problem-solver who simplifies problems to their core elements. B2B customer data experience a big plus. Advanced Salesforce product knowledge is also a plus. Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world. Accommodations If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form . Posting Statement Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.