2024 Inference Jobs - Page 5

Job Description: About Us At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities, and shareholders every day. One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We’re devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being. Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization. Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us! Global Business Services Global Business Services delivers Technology and Operations capabilities to Lines of Business and Staff Support Functions of Bank of America through a centrally managed, globally integrated delivery model and globally resilient operations. Global Business Services is recognized for flawless execution, sound risk management, operational resiliency, operational excellence and innovation. In India, we are present in five locations and operate as BA Continuum India Private Limited (BACI), a non-banking subsidiary of Bank of America Corporation and the operating company for India operations of Global Business Services. Process Overview* The Data Analytics Strategy platform and decision tool team is responsible for Data strategy for entire CSWT and development of platforms which supports the Data Strategy. Data Science platform, Graph Data Platform, Enterprise Events Hub are key platforms of Data Platform initiative. Job Description* We're looking for a highly skilled Container Platform Engineer to architect, implement, and manage our cloud-agnostic Data Science and Analytical Platform. Leveraging OpenShift (or other Kubernetes distributions) as the core container orchestration layer, you'll build a scalable and secure infrastructure vital for ML workloads and shared services. This role is key to establishing a robust hybrid architecture, paving the way for seamless future migration to AWS, Azure, or GCP. This individual will closely with data scientists, MLOps engineers, and platform teams to enable efficient model development, versioning, deployment, and monitoring within a multi-tenant environment. Responsibilities* Responsible for developing risk solutions to meet enterprise-wide regulatory requirements. Performs Monitoring and managing of large systems/platforms efficiently. Contributes to story refinement and definition of requirements. Participates in estimating work necessary to realize a story/requirement through the delivery lifecycle. Mentor team members, advocate best practices, and promote a culture if continuous improvement and innovation in engineering processes. Develop efficient utilities, automation frameworks, data science platforms that can be utilized across multiple Data Science teams. Propose/Build variety of efficient Data pipelines to support the ML Model building & deployment. Propose/Build automated deployment pipelines to enable self-help continuous deployment process for the Data Science teams. Analyze, understand, execute and resolve the issues in user scripts / model / code. Perform release and upgrade activities as required. Well versed in the open-source technology and aware of emerging 3rd party technology & tools in AI-ML space. Ability to fire fight, propose fix, guide the team towards day-to-day issues in production. Ability to train partner Data Science teams on frameworks and platform. Flexible with time and shift to support the project requirements. It doesn’t include any night shift. This position doesn’t include any L1 or L2 (first line of support) responsibility. Requirements* Education* Graduation / Post Graduation: BE/B.Tech/MCA/MTech Certifications If Any: Azure, AWS, GCP, Data Bricks Experience Range* 9+ Years Foundational Skills* Platform Design & Deployment: Design and deploy a comprehensive data science tech stack on OpenShift (or other Kubernetes distributions), including support for Jupyter notebooks, model training pipelines, inference services, and internal APIs. Cloud-Agnostic Architecture: Proven ability to build a cloud-agnostic container platform capable of seamless migration from on-prem OpenShift to cloud-native Kubernetes on AWS, Azure, or GCP. Container Platform Management: Expertise in configuring and managing multi-tenant namespaces, RBAC, network policies, and resource quotas within Kubernetes/OpenShift environments. API Gateway & Security: Hands-on experience with API gateway technologies like Apache APISIX (or similar tools) for managing and securing API traffic, including JWT/OAuth2-based authentication. MLOps Toolchain Support: Experience deploying and maintaining critical MLOps toolchains such as MLflow, Kubeflow, model registries, and feature stores. CI/CD & GitOps: Strong integration experience with GitOps and CI/CD tools (e.g., ArgoCD, Jenkins, GitHub Actions) for automating ML model and infrastructure deployment workflows. Microservices Deployment: Ability to deploy and maintain containerized microservices using Python frameworks (FastAPI, Flask) or Node.js to serve ML APIs. Observability: Ensure comprehensive observability across platform components using industry-standard tools like Prometheus, Grafana, and EFK/ELK stacks. Infrastructure as Code (IaC): Proficiency in automating platform provisioning and configuration using Infrastructure as Code tools (Terraform, Ansible, or Helm). Policy & Governance: Expertise with Open Policy Agent (OPA) or similar policy-as-code frameworks for implementing and enforcing robust governance policies. Desired Skills* Lead the design, development, and implementation of scalable, high-performance applications using Python/Java/Scala. Apply expertise in Machine Learning (ML) to build predictive models, enhance decision-making capabilities, and drive business insights. Collaborate with cross-functional teams to design, implement, and optimize cloud-based architectures on AWS and Azure. Work with large-scale distributed technologies like Apache Kafka, Apache Spark, and Apache Storm to ensure seamless data processing and messaging at scale. Provide expertise in Java multi-threading, concurrency, and other advanced Java concepts to ensure the development of high-performance, thread-safe, and optimized applications. Architect and build data lakes and data pipelines for large-scale data ingestion, processing, and analytics. Ensure integration of complex systems and applications across various platforms while adhering to best practices in coding, testing, and deployment. Collaborate closely with stakeholders to understand business requirements and translate them into technical specifications. Manage technical risk and work on performance tuning, scalability, and optimization of systems. Provide leadership to junior team members, offering guidance and mentorship to help develop their technical skills. Effective communication, Strong stakeholder engagement skills, Proven ability in leading and mentoring a team of software engineers in a dynamic environment. Security Architecture: Understanding of zero-trust security architecture and secure API design patterns. Model Serving Frameworks: Knowledge of specialized model serving frameworks like Triton Inference Server. Vector Databases: Familiarity with Vector databases (e.g., Redis, Qdrant) and embedding stores. Data Lineage & Metadata: Exposure to data lineage and metadata management using tools like DataHub or OpenMetadata. Work Timings* 11:30 AM to 8:30 PM IST Job Location* Chennai

Job Description Role: Manager - Data Analytics Location: New Delhi Chegg provides individualized learning support to students as they pursue their educational journeys. Available on demand 24/7 and powered by over a decade of learning insights, the Chegg platform offers students AI-powered academic support thoughtfully designed for education coupled with access to a vast network of subject matter experts who ensure quality. No matter the goal, level, or style, Chegg helps millions of students around the world learn with confidence by helping them build essential academic, life, and job skills to achieve success. Your analysis will provide valuable insights and identify key levers that materially improve how and what we create, as well as how we manage and deliver our content. Strong communication and analytic skills are critical for success in this role. Curiosity, persistence, creativity, and a desire to understand “the why” will make you successful in this role. Role Overview As a Manager – Data Analytics, you will lead a high-impact analytics team. With a strategic mindset and a strong technical foundation, you’ll drive data-informed decision-making, lead cross-functional projects, and build scalable analytical solutions to shape Chegg’s future. You’ll be responsible for leading and mentoring Data analysts, designing robust analytical frameworks, and engaging with senior stakeholders to inform key business decisions. This role demands strong leadership, deep analytical expertise, and excellent communication skills. Key Responsibilities Lead a team of analysts to deliver impactful insights across product, operations, and customer engagement. Develop and scale advanced analytical models to inform business strategy, product development, and customer experience. Own end-to-end project execution: from problem definition and data sourcing to insight generation and stakeholder presentation. Collaborate with product, engineering, marketing, and operations leaders to drive data-driven decisions across the company. Monitor KPIs and performance metrics to track success of initiatives and proactively identify areas for improvement. Mentor the team in using advanced tools (e.g., Python, SQL, Tableau, Amplitude) to create dashboards, reports, and predictive models. Influence data instrumentation decisions to ensure robust tracking and data quality. Evangelize data literacy across teams and foster a culture of curiosity, experimentation, and continuous learning. Qualifications 10+ years of experience in analytics, with at least 3+ years in a leadership or managerial role. Proven experience in building and scaling analytics teams and processes. Master’s degree preferred (in Statistics, Mathematics, Engineering, Economics, or a related field). Strong expertise in Python (mandatory), SQL, and BI tools like Tableau, Databricks, or PowerBI. Hands-on experience with forecasting models, statistical inference, and predictive modeling techniques. Deep understanding of data infrastructure, experimentation frameworks (A/B testing), and data governance. Experience with APIs, JSON data structures, and product analytics tools like Amplitude or Mixpanel. Excellent communication and storytelling skills; ability to simplify complex data into actionable business insights. Strategic thinker with a problem-solving mindset and a Why do we exist? Students are working harder than ever before to stabilize their future. Our recent research study called State of the Student shows that nearly 3 out of 4 students are working to support themselves through college and 1 in 3 students feel pressure to spend more than they can afford. We founded our business on provided affordable textbook rental options to address these issues. Since then, we’ve expanded our offerings to supplement many facets of higher educational learning through Chegg Study, Chegg Math, Chegg Writing, Chegg Internships, Thinkful Online Learning, and more to support students beyond their college experience. These offerings lower financial concerns for students by modernizing their learning experience. We exist so students everywhere have a smarter, faster, more affordable way to student. Video Shorts Life at Chegg: http://youtu.be/Fwf90zgaOLA Chegg Corporate Career Page: https://jobs.chegg.com/ Chegg India: http://www.cheggindia.com/ Chegg Israel: http://www.chegg.com/about/working-at-chegg/israel/ Thinkful (a Chegg Online Learning Service): https://www.thinkful.com/about/#careers Chegg out our culture and benefits! http://www.chegg.com/about/working-at-chegg/benefits/ Chegg is an equal opportunity employer

We're building a next generation agentic AI platform and need a talented, self-starting, experienced Senior developer. The role will require advanced AI manipulation (including prompt engineering) and model tuning. You will be part of a small multi-disciplinary team, solving problems that have never been solved before. Skills And Experience Excellent command of English reading, writing, and speaking Deep experience working with LLMs (OpenAI, Claude, Mistral, emphasis on open-source (smaller) models, etc.) Advanced prompt engineering across zero-, few-shot, and chain-of-thought paradigms Experience with Retrieval-Augmented Generation (RAG) pipelines Experience with model fine-tuning techniques, including LoRA, QLoRA, adapters, etc. Strong understanding of Agentic AI architectures, including multi-agent coordination, tool use, and planning Experience with Mixture of Experts (MoE) models and how to route, train, and serve them efficiently Experience with LLM tooling (LangChain, LlamaIndex, Transformers, etc.) Must be able to work UK office hours Desirable Skills Experience with TypeScript Experience with vector databases, embeddings, and hybrid search Experience with model hosting, inference infrastructure, and cloud-based deployment Experience with open-source LLMs and fine-tuning stacks (Axolotl, vLLM, etc.) Benefits “Yoodoo” - You can go offline and spend 2 hours of your work time every week on any activity that serves your mental or physical health; You will get 25 days paid Annual Leave per annum; Additional paid day off for festivals, your birthday, any celebration; Paid maternity leave; Paid paternity leave; Paid sick leave; Remote working; Union - who provide assistance and service to everyone at VDP Salary - Competitive market rate About VDP 🌟Founded 12 years ago in the UK, our company has a worldwide team that offers technology services. 👔 We help various clients, including those without their own developers. For them, we build entire teams to develop software from the ground up. We also assist clients who already have platforms and development teams but need help speeding up their work or starting new projects. 🛠️ Our skills include a broad range of technologies such as C#, Python, C++, Angular, React, Node.js, and both native and hybrid app development, as well as AI. Since we started, we have always worked remotely, so we don’t have an office, and everyone works from home. 🌲 We are a certified B Corp and have proven we are a force for good for our Employees, our Customers, are suppliers our Communities and the Environment. ❤️ 10% of what we make goes to our VDP Trust, helping to support projects for Women and Girls around the world. Through our work, our values and our actions, we aim to be a force for good, not just for ourselves and our customers, but for our communities and the world at large; We have four values that we all live by. These are Collaborate, Compassion, Honesty and Inclusion;

About FirstsourceFirstsource Solutions Limited, an RP-Sanjiv Goenka Group company (NSE: FSL, BSE: 532809, Reuters: FISO.BO, Bloomberg: FSOL:IN), is a specialized global business process services partner, providing transformational solutions and services spanning the customer lifecycle across Healthcare, Banking and Financial Services, Communications, Media and Technology, Retail, and other diverse industries. With an established presence in the US, the UK, India, Mexico, Australia, South Africa, and the Philippines, we make it happen for our clients, solving their biggest challenges with hyper-focused, domain-centered teams and cutting-edge tech, data, and analytics. Our real-world practitioners work collaboratively to deliver future-focused outcomes. Analytics and Data Science Delivery Responsibilities Lead Roles & Responsibilities We are seeking a Delivery Leader for Analytics and Data Science who can manage programs, from conceptualization to execution, across various domains including Machine Learning, Natural Language Processing (NLP), Forecasting, Experimental Design, Root Cause Analysis (RCA), and Data Visualization.Below are some of the core responsibilities associated with the role : Delivery : End-to-end delivery of Data Science Projects, POCs and other form of engagementsImplement and enforce best practices in model development, data processing, and deploymentEnsure efficient resource allocation, effective budget management, and adherence to project timelinesLead discussions with leadership to align business objectives, project plans, and address challenges proactively.Provide both functional and technical leadership to guide and mentor the team effectively Consulting : Identifying Analytics opportunities across client and internal operationsAssessment of Data & Tech readiness for deploying Analytical solutionsPreparing roadmap in terms of people, tools and capabilities that would be required for development Pre-Sales : Providing Delivery inputs (technical approach, pricing and implementation roadmap) for client RFPs/RFIsBuilding demonstratable capabilities Mandatory Qualifications & Skills 15+ Years of experience in Core Analytics and 5+ Years of experience in leading Analytics Programs Expert in Machine Learning Tools & Methodologies (such as Regression, Classification, Forecasting etc.) Expert in delivering projects in Natural Language Processing and allied areasExposure to Deep Learning frameworks such as Keras, Tensorflow etc. High degree of familiarity with at least one of the Cloud Technologies (e.g. – Azure, AWS, GCP etc.)Exposure to at least one of BI Stacks – Power BI/TableauHands-on experience across Python & SQL for Analytics development Experience in popular deployment methodologies and MLOps principles Experience in conducting statistical tests and designing experiments for causal inference Preferred Skills Familiarity with Generative AI solutions leveraging proprietary and Open-Source toolsExperience in developing and deploying Computer Vision solutions Familiarity with Data Engineering tools and methodologies (ETL, Data Pipelines etc.)Knowledge of Healthcare (Provider & Payer) & BFS Industry will be advantageous

Role Overview: As a Senior AI/ML Engineer, you will lead the design, development, and deployment of advanced machine learning models and AI solutions. Your expertise will drive innovation across various applications, from natural language processing (NLP) to deep learning and recommendation systems. You will collaborate with cross-functional teams to integrate AI capabilities into products and services, ensuring scalability, efficiency, and ethical standards. Key Responsibilities: Model Development & Deployment: Lead the end-to-end lifecycle of machine learning models, including data collection, preprocessing, model selection, training, evaluation, and deployment. Implement deep learning architectures (e.g., CNNs, RNNs, Transformers) and NLP models to solve complex problems. Optimize models for performance, scalability, and real-time inference. Collaboration & Leadership: Mentor and guide junior engineers and data scientists, fostering a culture of continuous learning and innovation. Collaborate with product managers, software engineers, and data engineers to align AI solutions with business objectives. Communicate complex technical concepts to both technical and non-technical stakeholders. Research & Innovation: Stay abreast of the latest advancements in AI/ML research and industry trends. Evaluate and integrate emerging technologies and methodologies to enhance model performance and capabilities. Contribute to the development of AI strategies and roadmaps. Ethics & Compliance: Ensure AI solutions adhere to ethical guidelines, data privacy regulations, and organizational standards. Implement fairness, accountability, and transparency in AI models to mitigate bias and ensure equitable outcomes. Technical Skills & Qualifications: Programming Languages: Proficiency in Python, with experience in libraries such as NumPy, Pandas, and Scikit-learn. Familiarity with other languages like Java, Scala, or C++ is a plus. Machine Learning Frameworks: Expertise in frameworks like TensorFlow, PyTorch, Keras, and Scikit-learn. Experience with MLOps tools and practices for model versioning, deployment, and monitoring. Data Engineering: Strong understanding of data pipelines, ETL processes, and working with large-scale datasets. Experience with SQL and NoSQL databases, as well as cloud platforms like AWS, GCP, or Azure. Soft Skills: Excellent problem-solving abilities and analytical thinking. Strong communication and interpersonal skills. Ability to work effectively in a collaborative, fast-paced environment. Educational Background: Bachelor's or master's degree in computer science, data science, machine learning, or a related field. Ph.D. is advantageous but not required. Preferred Experience: 8+ years in AI/ML engineering or related roles, with a proven track record of deploying production-grade models. Experience in specific domains such as healthcare, finance, or e-commerce is a plus. Why Join Us: Opportunity to work on cutting-edge AI projects with a talented team. Collaborative and inclusive work culture. Competitive compensation and benefits package. Continuous learning and professional development opportunities.

Job Family Data Science & Analysis (India) Travel Required Up to 25% Clearance Required None What You Will Do Design, train, and fine-tune advanced foundational models (text, audio, vision) using healthcare-and other relevant datasets, focusing on accuracy and context relevance. Collaborate with cross-functional teams (Business, engineering, IT) to seamlessly integrate AI/ML technologies into our solution offerings. Deploy, monitor, and manage AI models in a production environment, ensuring high availability, scalability, and performance. Continuously research and evaluate the latest advancements in AI/ML and industry trends to drive innovation. Ensure all AI solutions adhere to industry standards and regulatory requirements (i.e., HIPAA). Develop and maintain comprehensive documentation for AI models, including development, training, fine-tuning, and deployment procedures. Provide technical guidance and mentorship to junior AI engineers and team members. Collaborate with stakeholders to understand business needs and translate them into technical requirements for model fine-tuning and development. Select and curate appropriate datasets for fine-tuning foundational models to address specific use cases. Implement robust security protocols to protect sensitive data from breaches and unauthorized access. Ensure AI solutions can seamlessly integrate with existing systems and applications. What You Will Need Bachelors or master’s in computer science, Artificial Intelligence, Machine Learning, or a related field. 10+ year industry experience with minimum of 5 years of hands-on experience in AI/ML, with a demonstrable track record of training and deploying LLMs and other machine learning models. Strong proficiency in Python and familiarity with popular AI/ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers, etc.). Practical experience deploying and managing AI models in production environments, including expertise in serving and inference frameworks (Triton, TensorRT, VLLM, TGI, etc.). Experience in Voice AI applications, a solid understanding of healthcare data standards (FHIR, HL7, EDI) and regulatory compliance (HIPAA, SOC2) is preferred. Excellent problem-solving and analytical abilities, capable of tackling complex challenges and evaluating multiple factors. Exceptional communication and collaboration skills, enabling effective teamwork in a dynamic environment. Experience with cloud computing platforms (AWS, Azure) and containerization technologies (Docker, Kubernetes) is a plus. Familiarity with MLOps practices for continuous integration, continuous deployment (CI/CD), and automated monitoring of AI models. Delivered a minimum of 3 to 5 AI/LLM medium to large scale projects of significant value. What Would Be Nice To Have Experience with federated learning and privacy-preserving AI techniques. Familiarity with synthetic data generation for healthcare model training. Knowledge of healthcare is added advantage. Experience integrating AI with existing solutions. Experience working in regulated environments and with audit-ready documentation practices. Ability to evaluate and select GenAI models based on performance, cost, and compliance factors. What We Offer Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. About Guidehouse Guidehouse is an Equal Opportunity Employer–Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1-571-633-1711 or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or guidehouse@myworkday.com. Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse’s Ethics Hotline. If you want to check the validity of correspondence you have received, please contact recruiting@guidehouse.com. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant’s dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.

As an MLOps Engineer, you will be responsible for a wide range of engagements, listed below: • Can guide the team to build a scalable MLOps platform and work with business architects to implement and expand the MLOps setup. • Has worked on deploying ML models to production and has experience with model monitoring, inference, drift concepts, feature stores, etc. • Has a good understanding of how ML algorithms work and how to debug issues in the code. • Has deployed applications using containers and container orchestration • Manages conversations with client stakeholders to understand requirements and translate them into technical outcomes. • Responsible for bridging the gap between machine learning and software engineering, focusing on deployment, scaling, and management of ML models in production environments. • A developer focused on streamlining the process of developing, deploying, and maintaining ML systems to ensure they are efficient, scalable, and reliable. • Has a strong conceptual understanding of the ML lifecycle and various ML algorithms. • Has worked on at least one cloud platform and its ML-as-a-Service offerings. Qualifications: Technical: • Strong understanding of DevOps practices and skilled in developing end-to-end CI/CD pipelines • Execution knowledge of data modeling, databases (SQL and NoSQL), software development lifecycle practices, unit testing, functional programming, etc. • Experience with one or more ML-as-a-Service platforms, such as Azure DevOps, Dataiku, or equivalent open-source tools • Proficient in at least one programming language used in data engineering, such as Python • Strong knowledge of Snowflake • Experience working on at least one cloud platform Non-Technical: • Good business understanding • Logical thinking and problem-solving skills • Ability to collaborate effectively • Capable of analysing problems and developing actionable, tactical plans quickly • Good managerial skills and team leadership capabilities • Strong verbal and written communication skills • Good stakeholder management skills • Exercises independent judgment within defined practices and procedures • Demonstrated ability to mentor juniors

Job Description – AI Developer (Agentic AI Frameworks, Computer Vision & LLMs) Location (Hybrid - Bangalore) About the Role We’re seeking an AI Developer who specializes in agentic AI frameworks —LangChain, LangGraph, CrewAI, or equivalents—and who can take both vision and language models from prototype to production. You will lead the design of multi‑agent systems that coordinate perception (image classification & extraction), reasoning, and action, while owning the end‑to‑end deep‑learning life‑cycle (training, scaling, deployment, and monitoring). Key Responsibilities Scope What You’ll Do Agentic AI Frameworks (Primary Focus) Architect and implement multi‑agent workflows using LangChain, LangGraph, CrewAI, or similar. Design role hierarchies, state graphs, and tool integrations that enable autonomous data processing, decision‑making, and orchestration. Benchmark and optimize agent performance (cost, latency, reliability). Image Classification & Extraction Build and fine‑tune CNN/ViT models for classification, detection, OCR, and structured data extraction. Create scalable data‑ingestion, labeling, and augmentation pipelines. LLM Fine‑Tuning & Retrieval‑Augmented Generation (RAG) Fine‑tune open‑weight LLMs with LoRA/QLoRA, PEFT; perform SFT, DPO, or RLHF as needed. Implement RAG pipelines using vector databases (FAISS, Weaviate, pgvector) and domain‑specific adapters. Deep Learning at Scale Develop reproducible training workflows in PyTorch/TensorFlow with experiment tracking (MLflow, W&B). Serve models via TorchServe/Triton/KServe on Kubernetes, SageMaker, or GCP Vertex AI. MLOps & Production Excellence Build robust APIs/micro‑services (FastAPI, gRPC). Establish CI/CD, monitoring (Prometheus, Grafana), and automated retraining triggers. Optimize inference on CPU/GPU/Edge with ONNX/TensorRT, quantization, and pruning. Collaboration & Mentorship Translate product requirements into scalable AI services. Mentor junior engineers, conduct code and experiment reviews, and evangelize best practices. Minimum Qualifications B.S./M.S. in Computer Science, Electrical Engineering, Applied Math, or related discipline. 5+ years building production ML/DL systems with strong Python & Git . Demonstrable expertise in at least one agentic AI framework (LangChain, LangGraph, CrewAI, or comparable). Proven delivery of computer‑vision models for image classification/extraction. Hands‑on experience fine‑tuning LLMs and deploying RAG solutions. Solid understanding of containerization (Docker) and cloud AI stacks (AWS/Azure). Knowledge of distributed training, GPU acceleration, and performance optimization. ---------------------------------------------------------------------------------------------------------------------------------------------------------- Job Type: Full-time Pay: Up to ₹1,200,000.00 per year Experience: AI, LLM, RAG: 4 years (Preferred) Vector database, Image classification: 4 years (Preferred) containerization (Docker): 3 years (Preferred) ML/DL systems with strong Python & Git: 3 years (Preferred) LangChain, LangGraph, CrewAI: 3 years (Preferred) Location: Bangalore, Karnataka (Preferred) Work Location: In person

Company: Phenomenal AI Pvt. Ltd. Location: Remote / Mumbai-based (Hybrid options available) Experience Required: 2–3 years Type: Full-time About Us: Phenomenal AI is a pioneering text-to-video platform building state-of-the-art generative AI systems to convert natural language into dynamic, engaging video content. Our mission is to simplify storytelling at scale, enabling creators, educators, and enterprises to generate high-quality videos directly from text prompts. We are a fast-growing team of engineers, researchers, and designers passionate about shaping the future of content creation using AI. Job Description: We are looking for a skilled ML/AI Backend Engineer with 2–3 years of experience to join our core development team. The ideal candidate will be responsible for building the backend infrastructure that supports large generative models and scales the delivery of AI-generated videos to thousands of users. Key Responsibilities: • Develop and maintain robust backend systems for large-scale generative AI models. • Manage and process large datasets, including scraping, cleaning, and versioning. • Design and optimize inference pipelines for transformer or diffusion-based models. • Deploy and monitor AI models using cloud services (AWS, Azure, GCP). • Collaborate closely with ML researchers to integrate and scale new models in production. • Ensure security, reliability, and performance of backend services. • Handle containerization and infrastructure-as-code setups (e.g., Docker, Terraform). What We’re Looking For: • 2–3 years of experience in backend development with exposure to AI/ML systems. • Proficiency in Python and backend frameworks (e.g., FastAPI, Flask). • Experience with cloud platforms like AWS, Azure, or GCP. • Understanding of deploying and scaling ML models in production. • Familiarity with MLOps practices is a strong plus. • Experience working in fast-paced startup environments is a bonus. Working Hours: 10:30 am – 6:30 pm IST (Flexible for the right candidate). Perks & Benefits: • Work on cutting-edge generative AI problems in a rapidly growing domain. • Creative freedom to experiment and implement innovative ideas. • Collaborative, open-minded, and inclusive team culture. • Growth-oriented role with performance-linked opportunities. How to Apply: Send your resume and a short note about why you're interested to: research@phenomenalai.in

Job Summary: We are seeking a highly motivated and skilled LLM Engineer with 2 to 7 years of professional experience to join our growing AI team. The ideal candidate will have a strong background in natural language processing, machine learning, and hands-on experience in developing, deploying, and optimizing solutions built upon Large Language Models. You will play a crucial role in designing, implementing, and maintaining robust and scalable LLM-powered applications, contributing to the full lifecycle of our AI products. Key Responsibilities: LLM Application Development: Design, develop, and deploy innovative applications leveraging state-of-the-art Large Language Models (e.g., GPT, Llama, Gemini, Claude, etc.). This includes working with various LLM APIs and open-source models. Prompt Engineering & Optimization: Develop and refine advanced prompt engineering techniques to maximize LLM performance, accuracy, and desired output for specific use cases. Fine-tuning & Adaptation: Experiment with and implement strategies for fine-tuning pre-trained LLMs on custom datasets to improve performance for domain-specific tasks. Data Preparation & Curation: Work with diverse datasets for training, fine-tuning, and evaluating LLMs, ensuring data quality, relevance, and ethical considerations. Model Evaluation & Benchmarking: Design and execute robust evaluation methodologies to assess LLM performance, identify biases, and ensure alignment with business objectives. Implement A/B testing and other experimentation frameworks. Integration & Deployment: Integrate LLM-powered solutions into existing systems and deploy them to production environments, ensuring scalability, reliability, and low latency. Experience with MLOps practices is highly desirable. Performance Optimization: Identify and implement strategies for optimizing LLM inference, resource utilization, and cost efficiency. Research & Innovation: Stay abreast of the latest advancements in LLMs, NLP, and machine learning research. Proactively explore and propose new technologies and approaches to enhance our AI capabilities. Collaboration: Work closely with cross-functional teams including data scientists, software engineers, product managers, and researchers to deliver impactful AI solutions. Documentation: Create clear and concise documentation for models, code, and deployment procedures. Required Qualifications: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related quantitative field. 2-7 years of professional experience in a role focused on Machine Learning, Natural Language Processing, or AI development. Strong proficiency in Python and relevant ML/DL frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers). Hands-on experience with Large Language Models (LLMs) , including familiarity with their architectures (e.g., Transformers) and practical application. Experience with prompt engineering techniques and strategies. Solid understanding of NLP concepts, including text pre-processing, embeddings, semantic search, and information retrieval. Familiarity with cloud platforms (AWS, GCP, Azure) and their AI/ML services. Experience with version control systems (e.g., Git). Excellent problem-solving skills and the ability to work independently and as part of a team. Strong communication and interpersonal skills to articulate complex technical concepts to both technical and non-technical audiences. Preferred Qualifications (Bonus Points for): Experience with fine-tuning LLMs on custom datasets. Familiarity with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes). Experience with vector databases (e.g., Pinecone, Weaviate, Milvus) for RAG applications. Knowledge of various retrieval techniques for Retrieval Augmented Generation (RAG) systems. Understanding of ethical AI principles, bias detection, and fairness in LLMs. Contributions to open-source projects or relevant publications. Experience with distributed computing frameworks.

Job Title: Senior Backend & DevOps Engineer (AI-Integrated Products) Location: Remote Employment Type: Full Time/Freelance/Part Time Work Hours: Flexibile Work Timing About Us: We’re building AI-powered products that seamlessly integrate technology into everyday routines. We're now looking for a Senior Backend & DevOps Engineer who can help us scale Mobile Apps globally and architect the backend for it, while owning infrastructure, performance, and AI integrations. Responsibilities: Backend Engineering: Own and scale the backend architecture (Node.js/Express or similar) for Mobile Apps Build robust, well-documented, and performant APIs Implement user management, session handling, usage tracking, and analytics Integrate 3rd-party services including OpenAI, Whisper, and other LLMs Optimize app-server communication and caching for global scale DevOps & Infrastructure: Maintain and scale AWS/GCP infrastructure (EC2, RDS, S3, CloudFront/CDN, etc) Set up CI/CD pipelines (GitHub Actions preferred) for smooth deployment Monitor performance, set up alerts, and handle autoscaling across regions Manage cost-effective global infra scaling and ensure low-latency access Handle security (IAM, secrets management, HTTPS, CORS policies, etc) AI & Model Integration: Integrate LLMs like GPT-4, Mistral, Mixtral, and open-source models Support fine-tuning, inference pipelines, and embeddings Build offline inference support and manage transcription workflows (Whisper, etc) Set up and optimize vector DBs like Qdrant, Weaviate, Pinecone Requirements: 4+ years of backend experience with Node.js, Python, or Go 2+ years of DevOps experience with AWS/GCP/Azure, Docker, and CI/CD Experience deploying and managing AI/ML pipelines, especially LLMs and Whisper Familiarity with vector databases, embeddings, and offline inference Strong understanding of performance optimization, scalability, and observability Clear communication skills and a proactive mindset Bonus Skills: Experience working on mobile-first apps (React Native backend knowledge is a plus) Familiarity with Firebase, Vercel, Railway, or similar platforms Knowledge of data privacy, GDPR, and offline sync strategies Past work on productivity, journaling, or health/fitness apps Experience self-hosting LLMs or optimizing AI pipelines on edge/cloud Please share(Optional): A brief intro about you and your experience Links to your GitHub/portfolio or relevant projects Resume or LinkedIn profile Any AI/infra-heavy work you’re particularly proud of Contact : subham@binaryvlue.com

Frontend & Deployment Engineer – User Interface and Edge Expert 1.⁠ ⁠Role Objective: Responsible for creating intuitive user interfaces and managing edge deployments for AI applications. Must excel in developing user-friendly products that work seamlessly across various naval environments and devices. The engineer will be expected to design and build intuitive, responsive, and secure interfaces for naval AI applications. Package and deploy applications on warship consoles, edge devices, or Naval desktops/ tablets. Ensure usability under network-constrained, offline, or rugged field environments. 2.⁠ ⁠Key Responsibilities: 2.1. Develop UI interfaces for dashboards, alerts, geo-spatial visualization, analytics. 2.2. Integrate with AI outputs from backend (text, audio, image, event streams). 2.3. Build Electron-based desktop apps and Flutter-based mobile clients for offline use. 2.4. Ensure local caching, secure data handling, and session management. 2.5. Implement UI analytics to track user interaction and usage heatmaps (if permitted). 2.6. Work with end users (officers/sailors/operators) for field testing and UX feedback. 2.7. Ensure compliance with design constraints: minimal memory footprint, low power, rapid boot. 3.⁠ ⁠Educational Qualifications Essential Requirements: 3.1. B.Tech/M.Tech in Computer Science, Information Technology, or related field. 3.2. Strong foundation in user interface design and human-computer interaction. 3.3. Minimum 70% marks or 7.5 CGPA in relevant disciplines. Desired Professional Certifications: 3.4. Google UX Design Professional Certificate. 3.5. Adobe Certified Expert in UX Design. 3.6. Human-Computer Interaction certification. 3.7. Mobile app development certifications (iOS/Android) Core Skills & Tools: 4.⁠ ⁠Frontend Development: 4.1. Languages: JavaScript (ES6+), TypeScript, HTML5, CSS3, WebAssembly 4.2. Frameworks: React, Vue.js, Angular, Svelte, Next.js, Nuxt.js 4.3. Mobile Development: React Native, Flutter, Swift (iOS), Kotlin (Android) 4.4. UI Libraries: Material-UI, Ant Design, Chakra UI, Tailwind CSS 4.5. State Management: Redux, MobX, Vuex, Context API, Zustand 5.⁠ ⁠Visualization & Interactive Interfaces: 5.1. Data Visualization: D3.js, Chart.js, Plotly, Observable, Three.js 5.2. Maps & Geospatial: Leaflet, Mapbox, OpenLayers, Google Maps API 5.3. Real-time Updates: WebSocket, Server-Sent Events, Socket.io 5.4. Progressive Web Apps: Service Workers, offline capabilities, push notifications. 6.⁠ ⁠Edge Deployment: 6.1. Edge Computing: NVIDIA Jetson, Intel NUC, Raspberry Pi 6.2. Container Edge: K3s, MicroK8s, Docker on edge devices 6.3. Mobile Deployment: iOS App Store, Google Play Store deployment 6.4. Desktop Applications: Electron, Tauri, Progressive Web Apps 6.5. Embedded Systems: Basic embedded programming, hardware interfacing 7.⁠ ⁠Experience Requirements 7.1. Production experience with modern frontend frameworks 7.2. Mobile app development and deployment experience 7.3. Understanding of responsive design and accessibility standards 7.4. Experience with version control and collaborative development 7.5. Led frontend architecture decisions for complex applications 7.6. Experience with micro-frontend architectures 7.7. Performance optimization for web and mobile applications 7.8. Experience mentoring junior developers and conducting code reviews 8.⁠ ⁠Cross-Compatibility Requirements: 8.1. Consume APIs exposed by the backend with proper schema alignment. 8.2. Handle AI outputs (JSON, image, video) from inference modules designed by AI Engineer. 8.3. Provide test UI hooks to backend team for automation/integration testing. 8.4. Work with AI Engineer to display inference confidence, alerts.

Job Location City : Bangalore, Delhi, Chennai, Kochi, Noida, Gurugram Desired Competencies (Technical/Behavioral Competency): 5+ years of experience in software development, with a focus on Python API development. 2+ years of experience with TypeScript, including Visual Studio extension development or React JS. 1+ year Gen AI Application experience of Development / Deployment on Cloud 2+ years of experience with DevOps practices, CI/CD tools (e.g., Jenkins), and Kubernetes. Strong proficiency (2+ years) in Git and GitHub workflows. Experience with cloud platforms, preferably Azure or GCP. Good To Have: · Hands-on experience (2+) with containerization technologies (e.g., Docker). · Experience with Azure or GCP services, such as Kubernetes. · Experience supporting deployment artifacts in Kubernetes using Jenkins pipeline. · Knowledge of Linux/system administration. Responsibility of/Expectation of the Role: 1.Design, develop, and deploy scalable Python APIs using best practices and industry standards. 2 Develop and maintain TypeScript applications, including Visual Studio extensions, with UI exposure in React JS/TypeScript. 3 Design and develop AI-powered applications using Open AI inference endpoints and frameworks like LLAMA/Lang Chain. 4 Deploy and manage applications on Kubernetes, ensuring high availability and scalability. 5 Establish and maintain robust CI/CD pipelines using Git, GitHub workflows, and Jenkins. 6 Implement DevOps best practices and troubleshoot issuers related to API/TypeScript and applicationlook)

Job Description: We are seeking a highly skilled and experienced C++ Engineer to join our team. The primary responsibility will be converting existing Python-based computer vision and deep learning (CVDL) code into optimized, production-ready C++ code. The ideal candidate should be proficient in working with C++ frameworks and libraries, including TensorFlow, PyTorch, ONNX, MNN, NCNN, TensorFlow Lite (TFLite), MMDeploy, etc. The resulting C++ code will be used across Windows and Ubuntu environments, with a strong emphasis on cross-platform compatibility and performance optimization. Key Responsibilities: Convert Python-based CVDL (Computer Vision and Deep Learning) pipelines into optimized C++ implementations. Implement models and algorithms using C++ frameworks such as TensorFlow, PyTorch, ONNX, MNN, NCNN, TensorFlow Lite (TFLite), MMDeploy, and other relevant libraries. Optimize code for performance, ensuring efficient use of resources, especially in real-time processing pipelines. Ensure cross-platform compatibility, building C++ code that works seamlessly on both Windows and Ubuntu using CMakeLists. Debug, profile, and optimize deep learning inference pipelines, addressing issues related to memory usage, speed, and accuracy. Collaborate with AI teams to understand the Python codebase, gather requirements, and ensure the successful porting of features. Maintain up-to-date knowledge of the latest developments in C++ frameworks, deep learning inference engines, and performance optimization techniques. Requirements: Experience: - 5+ years of experience in C++ software development, specifically in converting Python code into C++. - 3 + years of experience with computer vision and deep learning frameworks such as TensorFlow, PyTorch, ONNX, MNN, NCNN, TensorFlow Lite (TFLite), MMDeploy , Mediapipe and Bazel build system. - Solid experience in cross-platform development for both Windows and Ubuntu using CMakeLists. Programming Skills: - Proficiency in C++ (C++11/14/17) with a deep understanding of memory management, multi-threading, and performance optimization. - Familiarity with Python, specifically in computer vision and deep learning applications, to interpret and convert code accurately. - Strong knowledge of CMake for building cross-platform applications. Technical Expertise: - Experience working with deep learning models and converting models between different formats (e.g., TensorFlow to ONNX, PyTorch to NCNN, etc.). - Experience with OpenCV and other related computer vision libraries. - Understanding of inference optimizations such as quantization, pruning, and model acceleration will be plus. Communication: - Strong problem-solving skills and the ability to work in a collaborative, fast-paced environment. - Ability to communicate effectively with cross-functional teams, including data scientists, ML engineers, and Python developers.

Role Description This is a full-time remote role for an AI Research Engineer specializing in Reinforcement Learning (RL). The AI Research Engineer will be responsible for developing and implementing state-of-the-art RL algorithms, collaborating on research projects, and integrating these algorithms into existing systems. Qualifications Full-stack engineering, from data engineering to model architecture, RL and deployment. Experience with performance engineering and identifying bottlenecks in RL training. Experience with tuning reward functions, hyper-parameters and exploration strategies to solve complex tasks with deep RL. 8+ years of Python programming experience. Nice to have Advanced degree (MS or PhD) in Computer Science or related field Experience with k8s, docker, GPU Performance / systems engineering and model inference.

About the Role We are seeking a visionary and technically astute Lead AI Architect to lead the architecture and design of scalable AI systems and next-generation intelligent platforms. As a core member of the leadership team, you will be responsible for driving end-to-end architectural strategy, model optimization, and AI infrastructure that powers mission-critical solutions across our product lines. This is a foundational role for someone passionate about architecting solutions involving RAG , SLMs/LLMs , multi-agent systems , and scalable model pipelines across cloud-native environments. Salary 30 - 45 LPA with additional benefits. Key Responsibilities Define and own the AI/ML architectural roadmap , aligning with product vision and technical goals. Architect and oversee implementation of RAG-based solutions , LLM/SLM fine-tuning pipelines , and multi-agent orchestration . Lead design of model training and inference pipelines ensuring scalability, modularity, and observability. Evaluate and select open-source and proprietary foundation models for fine-tuning, instruction tuning, and domain adaptation. Guide integration of vector databases, semantic search, and prompt orchestration frameworks (LangChain, LlamaIndex, etc.). Ensure best practices in model deployment, versioning, monitoring , and performance optimization (GPU utilization, memory efficiency, etc.). Collaborate with Engineering, DevOps, Product, and Data Science teams to bring AI features to production. Mentor mid-level engineers and interns; contribute to technical leadership and code quality . Maintain awareness of latest research, model capabilities, and trends in AI. Required Skills & Qualifications 6+ years of hands-on experience in AI/ML architecture and model deployment. Expert-level knowledge of Python and libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and FastAPI. Deep understanding of LLMs/SLMs, embedding models, tokenization strategies, fine-tuning, quantization, and LoRA/QLoRA. Proven experience with Retrieval-Augmented Generation (RAG) pipelines and vector DBs like FAISS, Pinecone, or Weaviate. Strong grasp of system design, distributed training, MLOps, and scalable cloud-based infrastructure (AWS/GCP/Azure). Experience with containerization (Docker), orchestration (Kubernetes), and experiment tracking (MLFlow, W&B). Experience in building secure and performant REST APIs , deploying and monitoring AI services in production. Nice to Have Exposure to multi-agent frameworks, task planners, or LangGraph. Experience leading AI platform teams or architecting enterprise-scale ML platforms. Familiarity with Data Governance, Responsible AI, and model compliance requirements. Published papers, open-source contributions, or patents in the AI/ML domain. Why Join Us Be at the forefront of innovation in AI and language intelligence. Influence strategic technical decisions and drive company-wide AI architecture. Lead a growing AI team in a high-impact, fast-paced environment. Competitive compensation, equity options, and leadership opportunity.

About the Role We are seeking a hands-on AI/ML Engineer with deep expertise in Retrieval-Augmented Generation (RAG) agents , Small Language Model (SLM) fine-tuning , and custom dataset workflows . You'll work closely with our AI research and product teams to build production-grade models, deploy APIs, and enable next-gen AI-powered experiences. Key Responsibilities Design and build RAG-based solutions using vector databases and semantic search. Fine-tune open-source SLMs (e.g., Mistral, LLaMA, Phi, etc.) on custom datasets. Develop robust training and evaluation pipelines with reproducibility. Create and expose REST APIs for model inference using FastAPI . Build lightweight frontends or internal demos with Streamlit for rapid validation. Analyze model performance and iterate quickly on experiments. Document processes and contribute to knowledge-sharing within the team. Must-Have Skills 3–5 years of experience in applied ML/AI engineering roles. Expert in Python and common AI frameworks (Transformers, PyTorch/TensorFlow). Deep understanding of RAG architecture, vector stores (FAISS, Pinecone, Weaviate). Experience with fine-tuning transformer models and instruction-tuned SLMs. Proficient with FastAPI for backend API deployment and Streamlit for prototyping. Knowledge of tokenization, embeddings, training loops, and evaluation metrics. Nice to Have Familiarity with LangChain, Hugging Face ecosystem, and OpenAI APIs. Experience with Docker, GitHub Actions, and cloud model deployment (AWS/GCP/Azure). Exposure to experiment tracking tools like MLFlow, Weights & Biases. What We Offer Build core tech for next-gen AI products with real-world impact. Autonomy and ownership in shaping AI components from research to production. Competitive salary, flexible remote work policy, and a growth-driven environment.

Gen AI Technical Architect_Full-Time_Hyderabad (Work from office) Job Title: Gen AI Technical Architect Job Type: Full-Time Location: Hyderabad (Work from office) Experience: 12-16 Years Primary Skills: Gen Ai, Azure Open Ai, Python and which are mentions in cheat sheet Job Description: Gen AI Technical Architect Generative AI Architect will play a pivotal role in designing, developing, and implementing advanced generative AI solutions that drive significant business impact for our clients. This role offers the exciting opportunity to work at the forefront of AI innovation, leveraging the power of AI. Role Overview: The Generative AI Architect will be responsible for the end-to-end architecture, design, and deployment of scalable and robust generative AI systems. This includes conceptualizing solutions, selecting appropriate models and frameworks, overseeing development, and ensuring the successful integration of generative AI capabilities into existing and new platforms. You will work closely with business stakeholders to translate complex requirements into high-performance AI solutions. Key Responsibilities: Architect and Design Generative AI Solutions : Lead the architectural design of generative AI systems, including model selection (LLMs), RAG and fine-tuning approaches. Azure AI Expertise : Design and deploy scalable AI solutions leveraging a comprehensive suite of Azure AI services. Python Development : Write clean, efficient, and maintainable Python code for data processing, automation, and API integrations. Model Optimization and Performance : Optimize generative AI models for performance, scalability, and cost-efficiency. Data Strategy: Design data architectures and pipelines to ingest, process, and prepare data for generative AI model training and inference, utilizing Azure data services. Integration and Deployment: Oversee the integration of generative AI models into existing enterprise systems and applications. Implement robust MLOps practices, CI/CD pipelines (e.g., Azure DevOps, GitHub, Jenkins), and containerization (Docker, Kubernetes) for seamless deployment. Technical Leadership & Mentorship: Provide technical leadership and guidance to development teams, fostering best practices in AI model development, deployment, and maintenance. Research and Innovation: Stay abreast of the latest advancements in generative AI technologies, research methodologies, and industry trends. Drive proof-of-concepts (PoCs) and pilot implementations for new AI capabilities. Collaboration and Communication: Collaborate effectively with cross-functional teams, including product managers, data scientists, software engineers, and business analysts, to ensure AI solutions align with business goals and deliver tangible value. Articulate complex technical concepts to non-technical stakeholders. Required Skills and Qualifications: Minimum of 12-16 years of experience in IT, with at least 3+ years specifically focused on Gen AI architecture and development. Technical Proficiency: Deep expertise in Azure Cloud Platform and its AI services Strong proficiency in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, Hugging Face, LangChain, LlamaIndex). Solid understanding of large language models (LLMs), transformer architectures, diffusion models, and other generative AI techniques. Hands-on experience with prompt engineering, RAG pipelines, and vector databases (e.g., Pinecone, Weaviate, Chroma). Experience with MLOps, CI/CD, and deployment tools (Azure DevOps, GitHub, Kubernetes). Familiarity with RESTful API design and development. Architectural Principles: Strong understanding of cloud architecture, microservices architecture, and design patterns. Problem-Solving: Excellent analytical and problem-solving skills with the ability to think critically and creatively. Communication: Exceptional communication and interpersonal skills, with the ability to convey complex technical concepts clearly to both technical and non-technical audiences. Team Player: Ability to work collaboratively in a fast-paced, agile environment and lead projects with multiple stakeholders. Desirable: Relevant Azure AI certifications Experience with other cloud platforms (AWS). Experience with fine-tuning LLMs for specific use cases. Contributions to open-source AI projects or publications in AI/ML.

Senior Software Engineer Bangalore, Karnataka, India Date posted Jul 28, 2025 Job number 1849823 Work site Up to 50% work from home Travel 0-25 % Role type Individual Contributor Profession Software Engineering Discipline Software Engineering Employment type Full-Time Overview Microsoft Silicon, Cloud Hardware, and Infrastructure Engineering (SCHIE) is the team behind Microsoft’s expanding Cloud Infrastructure and responsible for powering Microsoft’s “Intelligent Cloud” mission. SCHIE delivers the core infrastructure and foundational technologies for Microsoft's over 200 online businesses including Bing, MSN, Office 365, Xbox Live, Teams, OneDrive, and the Microsoft Azure platform globally with our server and data center infrastructure, security and compliance, operations, globalization, and manageability solutions. Our focus is on smart growth, high efficiency, and delivering a trusted experience to customers and partners worldwide and we are looking for passionate engineers to help achieve that mission. As Microsoft's cloud business continues to grow the ability to deploy new offerings and hardware infrastructure on time, in high volume with high quality and lowest cost is of paramount importance. To achieve this goal, the SW/FW Centre of Excellence team is instrumental in defining and delivering operational measures of success for hardware manufacturing, improving the planning process, quality, delivery, scale and sustainability related to Microsoft cloud hardware. We are looking for seasoned engineers with a dedicated passion for customer focused solutions, insight and industry knowledge to envision and implement future technical solutions that will manage and optimize the Cloud infrastructure. We are looking for a highly motivated Senior Software Engineer with a track record in Cloud Service development to come help us develop and light up innovative AI-based solutions to improve engineering efficiency across development, validation and monitoring. To be successful in this role, you must have a great track record of delivering quality results to customers, an engineering mindset, an innate aptitude for agility, and technical excellence in software engineering. #SCHIE Qualifications Required Qualifications Bachelor’s degree in Computer Science, Computer Engineering, or a related field. 6+ years of industry experience in AI/ML engineering using platforms and languages/frameworks such as Python, Semantic Kernel, AutoGen, Azure AI Foundry, Mem0, Azure AI Search. Proven experience in designing, building, and deploying AI agents across the autonomy spectrum—from retrieval-based to task-oriented and autonomous agents. Strong background in developing web applications and services that integrate AI/ML models for business insights and automation. Preferred Qualifications Hands-on experience with large language models (LLMs), including training, fine-tuning, and inference optimization for multi-billion parameter models. Familiarity with the full ML lifecycle: data engineering, model training, evaluation, deployment, and monitoring. Understanding of embedded systems, firmware development, OS concepts is a strong plus. Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter. Responsibilities Design and implement AI agents using modern agent development frameworks (e.g., Semantic Kernel, AutoGen, AI Foundry). Build scalable, production-grade AI services that integrate with enterprise systems and workflows. Collaborate with cross-functional teams to define agent capabilities, communication protocols, and compliance requirements. Optimize agent performance for real-time inference and continuous learning. Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.  Industry leading healthcare  Educational resources  Discounts on products and services  Savings and investments  Maternity and paternity leave  Generous time away  Giving programs  Opportunities to network and connect Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Job Information Industry Health Care Salary 0 - 3 K Date Opened 07/28/2025 Job Type Full time Work Experience 1-3 years City Bangalore North State/Province Karnataka Country India Zip/Postal Code 560048 Job Description Job Description: AI/ML Engineer Key Responsibilities Design, develop, and deploy deep learning and machine learning models, particularly convolutional neural networks (CNNs) for medical image analysis. Build scalable and efficient training and inference pipelines using frameworks like TensorFlow and PyTorch. Manage and deploy DL/ML solutions using local virtual machines (VMs); experience with cloud platforms like AWS and Azure is a plus. Containerize DL/ML workflows using Docker and implement CI/CD pipelines for model delivery. Optimize models for accuracy and speed; conduct A/B testing and validation with real-world radiology data. Collaborate with radiologists and software teams to integrate AI models into teleradiology platforms. Develop and maintain API integrations, including FastAPI-based services and interoperability with legacy systems. Monitor and maintain deployed models to ensure consistent performance in clinical environments. Requirements Must-Have Skills Proficient in Deep Learning and Machine Learning techniques. Strong experience with TensorFlow and PyTorch. Solid background in image processing and computer vision, especially with CNN architectures. Proficiency with Docker and experience with CI/CD pipelines. Excellent programming skills in Python and experience with relevant ML libraries. Understanding of data pipelines and handling large-scale medical imaging datasets. Nice to Have Experience deploying ML models on cloud platforms such as AWS and Azure. Experience with Kubernetes or orchestration frameworks. Familiarity with MLOps tools and workflows. Experience with distributed training or federated learning. Contributions to healthcare AI research or open-source projects. Education & Experience Bachelor’s or Master’s degree in Computer Science, Biomedical Engineering, Data Science, or related field. 1+ years of experience building and deploying machine learning solutions in production, preferably in a healthcare or radiology setting. Why Join Us? Opportunity to work on transformative AI applications in healthcare and radiology. Collaborative and mission-driven team environment. Access to advanced medical imaging datasets. Interested can apply to nanda.k@telradsol.com

Job Description Role: Manager - Data Analytics Location: New Delhi Chegg provides individualized learning support to students as they pursue their educational journeys. Available on demand 24/7 and powered by over a decade of learning insights, the Chegg platform offers students AI-powered academic support thoughtfully designed for education coupled with access to a vast network of subject matter experts who ensure quality. No matter the goal, level, or style, Chegg helps millions of students around the world learn with confidence by helping them build essential academic, life, and job skills to achieve success. Your analysis will provide valuable insights and identify key levers that materially improve how and what we create, as well as how we manage and deliver our content. Strong communication and analytic skills are critical for success in this role. Curiosity, persistence, creativity, and a desire to understand “the why” will make you successful in this role. Role Overview: As a Manager – Data Analytics, you will lead a high-impact analytics team. With a strategic mindset and a strong technical foundation, you’ll drive data-informed decision-making, lead cross-functional projects, and build scalable analytical solutions to shape Chegg’s future. You’ll be responsible for leading and mentoring Data analysts, designing robust analytical frameworks, and engaging with senior stakeholders to inform key business decisions. This role demands strong leadership, deep analytical expertise, and excellent communication skills. Key Responsibilities: Lead a team of analysts to deliver impactful insights across product, operations, and customer engagement. Develop and scale advanced analytical models to inform business strategy, product development, and customer experience. Own end-to-end project execution: from problem definition and data sourcing to insight generation and stakeholder presentation. Collaborate with product, engineering, marketing, and operations leaders to drive data-driven decisions across the company. Monitor KPIs and performance metrics to track success of initiatives and proactively identify areas for improvement. Mentor the team in using advanced tools (e.g., Python, SQL, Tableau, Amplitude) to create dashboards, reports, and predictive models. Influence data instrumentation decisions to ensure robust tracking and data quality. Evangelize data literacy across teams and foster a culture of curiosity, experimentation, and continuous learning. Qualifications: 10+ years of experience in analytics, with at least 3+ years in a leadership or managerial role. Proven experience in building and scaling analytics teams and processes. Master’s degree preferred (in Statistics, Mathematics, Engineering, Economics, or a related field). Strong expertise in Python (mandatory), SQL, and BI tools like Tableau, Databricks, or PowerBI. Hands-on experience with forecasting models, statistical inference, and predictive modeling techniques. Deep understanding of data infrastructure, experimentation frameworks (A/B testing), and data governance. Experience with APIs, JSON data structures, and product analytics tools like Amplitude or Mixpanel. Excellent communication and storytelling skills; ability to simplify complex data into actionable business insights. Strategic thinker with a problem-solving mindset and a Why do we exist? Students are working harder than ever before to stabilize their future. Our recent research study called State of the Student shows that nearly 3 out of 4 students are working to support themselves through college and 1 in 3 students feel pressure to spend more than they can afford. We founded our business on provided affordable textbook rental options to address these issues. Since then, we’ve expanded our offerings to supplement many facets of higher educational learning through Chegg Study, Chegg Math, Chegg Writing, Chegg Internships, Thinkful Online Learning, and more to support students beyond their college experience. These offerings lower financial concerns for students by modernizing their learning experience. We exist so students everywhere have a smarter, faster, more affordable way to student. About Us What is Chegg? An ‘always on’ digital learning platform. Chegg puts students first…Everything we build in this company is student-focused, making us the leading student-first connected learning platform. Chegg strives to improve the overall return on investment in education by helping students learn more in less time and at a lower cost. This is achieved by providing students a multitude of educational tools from affordable textbook rentals to Chegg Study which supplements their learning through 24/7 tutor access, step-by-step help with questions, and more. Chegg is a publicly-held company based in Santa Clara, California and trades on the NYSE under the symbol CHGG.

Designation: Senior Analyst Level: L2 Experience: 4 to 7 years Location: Chennai Job Description: We are seeking a highly skilled and motivated results-driven Senior Analyst with 4+ years of experience to join a fast-paced collaborative team at LatentView Analytics working in the financial services domain. Responsibilities: Drive measurement strategy and lead E2E process of A/B testing for areas of web optimization such as landing pages, user funnel, navigation, checkout, product lineup, pricing, search and monetization opportunities. Analyze web user behavior at both visitor and session level using clickstream data by anchoring to key web metrics and identify user behavior through engagement and pathing analysis Leverage AI/GenAI tools for automating tasks and building custom implementations Use data, strategic thinking and advanced scientific methods including predictive modeling to enable data-backed decision making for Intuit at scale Measure performance and impact of various product releases Demonstrate strategic thinking and systems thinking to solve business problems and influence strategic decisions using data storytelling. Partner with GTM, Product, Engineering, Design, Engineering teams to drive analytics projects end to end Build models to identify patterns in traffic and user behavior to inform acquisition strategies and optimize for business outcomes Skills: +5 years of experience working in web, product, marketing, or other related analytics fields to solve for marketing/product business problems +4 years of experience in designing and executing experiments (A/B and multivariate) with a deep understanding of the stats behind hypothesis testing Proficient in alternative A/B testing methods like DiD, Synthetic control and other causal inference techniques +5 years of technical proficiency in SQL, Python or R and data visualization tools like tableau +5 years of experience in manipulating and analyzing large complex datasets (e.g. clickstream data), constructing data pipelines (ETL) and working on big data technologies (e.g., Redshift, Spark, Hive, BigQuery) and solutions from cloud platforms and visualization tools like Tableau +3 years of experience in web analytics, analyzing website traffic patterns and conversion funnels +5 years of experience in building ML models (eg: regression, clustering, trees) for personalization applications Demonstrate ability to drive strategy, execution and insights for AI native experiences across the development lifecycle (ideation, discovery, experimentation, scaling) Outstanding communication skills with both technical and non-technical audiences Ability to tell stories with data, influence business decisions at a leadership level, and provide solutions to business problems Ability to manage multiple projects simultaneously to meet objectives and key deadlines Job Snapshot Updated Date 28-07-2025 Job ID J_3917 Location Chennai, Tamil Nadu, India Experience 4 - 7 Years Employee Type Permanent

You might be a fit if you have ● 5 + yrs production ML / data-platform engineering (Python or Go/Kotlin). ● Deployed agentic or multi-agent systems (e.g., micro-policy nets, bandit ensembles) and reinforcement-learning pipelines at scal (ad budget, recommender, or game AI). ● Fluency with BigQuery / Snowflake SQL & ML plus streaming (Kafka / Pub/Sub). ● Hands-on LLM fine-tuning using LoRA/QLoRA and proven prompt-engineering skills (system / assist hierarchies, few-shot, prompt compression). ● Comfort running GPU & CPU model serving on GCP (Vertex AI, GKE, or bare-metal K8s). ● Solid causal-inference experience (CUPED, diff-in-diff, synthetic control, uplift). ● CI/CD, IaC (Terraform or Pulumi) & observability chops (Prometheus, Grafana). ● Bias toward shipping working software over polishing research papers. Bonus points for: ● Postal/geo datasets, ad-tech, or martech domain exposure. ● Packaging RL models as secure micro-services. ● VPC-SC, NIST, or SOC-2 controls in a regulated data environment. ● Green-field impact – architect the learning stack from scratch. ● Moat-worthy data – 260 M+ US consumer graph tying offline & online behavior. ● Tight feedback loops – your models go live in weeks, optimizing large amounts of marketing spend daily.

Job Description: AI/ML Engineer Key Responsibilities · Design, develop, and deploy deep learning and machine learning models, particularly convolutional neural networks (CNNs) for medical image analysis. · Build scalable and efficient training and inference pipelines using frameworks like TensorFlow and PyTorch. · Manage and deploy DL/ML solutions using local virtual machines (VMs); experience with cloud platforms like AWS and Azure is a plus. · Containerize DL/ML workflows using Docker and implement CI/CD pipelines for model delivery. · Optimize models for accuracy and speed; conduct A/B testing and validation with real-world radiology data. · Collaborate with radiologists and software teams to integrate AI models into teleradiology platforms. · Develop and maintain API integrations, including FastAPI-based services and interoperability with legacy systems. · Monitor and maintain deployed models to ensure consistent performance in clinical environments. Requirements Must-Have Skills · Proficient in Deep Learning and Machine Learning techniques. · Strong experience with TensorFlow and PyTorch. · Solid background in image processing and computer vision, especially with CNN architectures. · Proficiency with Docker and experience with CI/CD pipelines. · Excellent programming skills in Python and experience with relevant ML libraries. · Understanding of data pipelines and handling large-scale medical imaging datasets. Nice to Have · Experience deploying ML models on cloud platforms such as AWS and Azure. · Experience with Kubernetes or orchestration frameworks. · Familiarity with MLOps tools and workflows. · Experience with distributed training or federated learning. · Contributions to healthcare AI research or open-source projects. Education & Experience · Bachelor’s or Master’s degree in Computer Science, Biomedical Engineering, Data Science, or related field. · 1+ years of experience building and deploying machine learning solutions in production, preferably in a healthcare or radiology setting. Why Join Us? · Opportunity to work on transformative AI applications in healthcare and radiology. · Collaborative and mission-driven team environment. · Access to advanced medical imaging datasets. Interested can apply to nanda.k@telradsol.com

Location: Remote | CTC: 5,00,000-7,00,000 LPA + ESOPs About Us : We're on a mission to revolutionize sports analytics by integrating cutting-edge AI into real-time and post-match video analysis. Our platform delivers powerful insights to enhance athlete performance, optimize coaching strategies, and engage fans like never before. Join us at the intersection of technology and athletic excellence. Role Overview : As an AI Sports Analyst / Computer Vision Engineer , you'll play a pivotal role in our technology team, developing intelligent systems that analyze sports video footage to uncover performance metrics, tactical patterns, and game-changing insights. Your innovations will help athletes train smarter, enable coaches to make data-driven decisions, and transform how fans connect with the game — making a real impact on the future of sports. Job Responsibilities As our AI Engineer, you will: ✅ Build and optimize computer vision models to detect and track players, ball, referee, and other key entities in sports footage ✅ Develop event recognition models ✅ Implement pose estimation and action recognition algorithms for performance analytics ✅ Work with multi-camera setups to perform 3D player reconstruction and spatial analysis ✅ Deploy models in real-time pipelines and optimize for low-latency inference ✅ Integrate AI pipelines with front-end visualization dashboards ✅ Collaborate with frontend/backend devs, data annotators, and sports analysts ✅ Stay up to date with state-of-the-art research in vision-based sports analytics Preferred Skills : ⏱️ Real-time inference pipeline design ⚽ Prior work on sports 🖥️ Familiarity with multi-view 3D reconstruction 📍 Pose estimation or skeletal keypoint tracking 🧪 Background in Reinforcement Learning for player movement prediction (optional) 💡 Research publications or GitHub repos in sports AI 📦 Experience with MLOps tools: Weights & Biases, MLflow, DVC