FactSet creates flexible, open data and software solutions for over 200,000 investment professionals worldwide, providing instant access to financial data and analytics that investors use to make crucial decisions. At FactSet, our values are the foundation of everything we do. They express how we act and operate, serve as a compass in our decision-making, and play a big role in how we treat each other, our clients, and our communities. We believe that the best ideas can come from anyone, anywhere, at any time, and that curiosity is the key to anticipating our clients’ needs and exceeding their expectations. Your Team's Impact Join our dynamic Machine Learning and AI team, where we build innovative models and solutions that drive business transformation and unlock new opportunities. You’ll be at the forefront of AI-powered initiatives, collaborating closely with product teams to shape the future of data-driven insights. This position offers high visibility and the chance to directly influence key decisions across the organization. You will report to the Manager of AI. Working Mode: Hybrid (3 days mandatory Office) What You'll Do Technical Leadership & Strategy Lead the design, development, and deployment of machine learning models and systems at scale. Define and drive the technical roadmap for ML initiatives in alignment with business goals. Evaluate and select appropriate ML techniques, architectures, and tools for various problems (e.g., NLP, CV, tabular data). Ensure robust experimentation, validation, and performance benchmarking practices. Team Guidance & Mentorship Mentor and support junior and mid-level ML engineers, guiding them on model development, research approaches, and code quality. Conduct technical reviews of models, pipelines, and code to ensure high standards. Promote a culture of continuous learning, innovation, and scientific rigor within the team. System & Pipeline Development Architect and implement scalable ML pipelines for training, validation, inference, and monitoring. Collaborate with data engineers to ensure high-quality data ingestion, feature engineering, and labeling workflows. Contribute to MLOps practices by building reproducible, testable, and maintainable model delivery frameworks. Assist in designing, developing, and implementing machine learning models for real-world applications. Work on data collection, preprocessing, feature engineering, and model evaluation tasks. Collaborate with cross-functional teams including Data Science, Software Engineering, and Product. Perform exploratory data analysis (EDA) and prepare datasets for training/testing. Contribute to the deployment and monitoring of models in production environments. Write clean, efficient, and well-documented code in Python or similar languages. Stay updated with the latest developments in AI/ML research and tools. Assist in model optimization, hyperparameter tuning, and performance scaling. Stay current with the latest industry trends and technologies, contributing innovative ideas to ongoing projects. Test and validate models to ensure their reliability and effectiveness in production environments. Work with large datasets to extract meaningful insights using various statistical and ML techniques. Required Skills What We're Looking For Bachelor’s or master’s degree in computer science, Engineering, or a related field is required. 5+ years of experience in software development, with a focus on systems handling large-scale data operations. Strong foundation in Machine Learning concepts (supervised/unsupervised learning, regression, classification, clustering, etc.). Good programming skills in Python (or similar languages like R, Java, C++). Hands-on experience with ML libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch, Keras). Understanding of data structures, algorithms, and basic mathematics/statistics and database management systems. Excellent verbal and written communication skills, capable of articulating complex concepts to technical and non-technical audiences. Familiarity with data handling tools (e.g., Pandas, NumPy, SQL). Good analytical, problem-solving, and communication skills. Ability to learn new technologies quickly and work independently or as part of a team. Ability to work collaboratively in a team environment, contributing to group success while expanding personal skills. Desired Skills Exposure to deep learning, NLP, computer vision, or reinforcement learning projects (academic or internships). Knowledge of cloud platforms like AWS, Azure, or GCP. Familiarity with version control systems (e.g., Git). Understanding of MLOps concepts and pipelines (bonus) What's In It For You At FactSet, our people are our greatest asset, and our culture is our biggest competitive advantage. Being a FactSetter means: The opportunity to join an S&P 500 company with over 45 years of sustainable growth powered by the entrepreneurial spirit of a start-up. Support for your total well-being. This includes health, life, and disability insurance, as well as retirement savings plans and a discounted employee stock purchase program, plus paid time off for holidays, family leave, and company-wide wellness days. Flexible work accommodations. We value work/life harmony and offer our employees a range of accommodations to help them achieve success both at work and in their personal lives. A global community dedicated to volunteerism and sustainability, where collaboration is always encouraged, and individuality drives solutions. Career progression planning with dedicated time each month for learning and development. Business Resource Groups open to all employees that serve as a catalyst for connection, growth, and belonging. Learn More About Our Benefits Here. Salary is just one component of our compensation package and is based on several factors including but not limited to education, work experience, and certifications. Company Overview: FactSet (NYSE:FDS | NASDAQ:FDS) helps the financial community to see more, think bigger, and work better. Our digital platform and enterprise solutions deliver financial data, analytics, and open technology to more than 8,200 global clients, including over 200,000 individual users. Clients across the buy-side and sell-side, as well as wealth managers, private equity firms, and corporations, achieve more every day with our comprehensive and connected content, flexible next-generation workflow solutions, and client-centric specialized support. As a member of the S&P 500, we are committed to sustainable growth and have been recognized among the Best Places to Work in 2023 by Glassdoor as a Glassdoor Employees’ Choice Award winner. Learn more at www.factset.com and follow us on X and LinkedIn. At FactSet, we celebrate difference of thought, experience, and perspective. Qualified applicants will be considered for employment without regard to characteristics protected by law. Show more Show less

Location: Gurugram, India (On-site/Hybrid) Type: Full-Time | 5+ Years Experience | AI & Product Engineering Hubnex Labs is seeking a highly skilled Machine Learning Engineer with strong capabilities in Full Stack Development to lead the development and deployment of production-grade AI systems. This role requires expertise in building end-to-end ML pipelines—from data preprocessing to deployment—while also contributing to the full stack of software platforms that power our solutions. Key Responsibilities Machine Learning & Data Science Understand business goals and translate them into ML-based solutions Develop, analyze, and compare machine learning algorithms for various problem statements Build robust validation strategies and design appropriate preprocessing and feature engineering pipelines Perform data exploration, visualization, and quality verification, including data cleaning and augmentation Train models, tune hyperparameters, and interpret model performance Analyze errors and design strategies to improve model robustness Discover and utilize public datasets for model training and benchmarking Deploy models into production environments with real-world performance and latency considerations Software & System Development Design and develop end-to-end production systems, including backend APIs and frontend interfaces Maintain full stack web applications, ensuring seamless ML model integration Ensure efficient use of hardware resources for training and inference Collaborate cross-functionally with engineering, product, and design teams Technical Skills Required 5+ years of hands-on experience in machine learning and full stack development Proficiency in Python and ML libraries like scikit-learn, pandas, NumPy, etc. Deep learning experience using TensorFlow, Keras, or equivalent frameworks Proficiency with OpenCV and image/video processing techniques Experience with data visualization tools and big data handling Strong understanding of data pipelines, feature engineering, and augmentation techniques Proficiency in Full Stack Web Development (e.g., React, Node.js, Express, MongoDB or similar) Experience deploying models using REST APIs, Flask/FastAPI, Docker, etc. Familiarity with Linux environments and GPU-accelerated compute systems Understanding of hardware requirements and optimization for real-time ML performance Why Join Hubnex Labs? Work on impactful AI products deployed in real-world use cases Be a part of a fast-growing tech consulting and product innovation company Collaborate with a diverse team of engineers, data scientists, and innovators Flexible and collaborative culture based in Gurugram, with hybrid work options Ideal Candidate Passionate about building smart systems that go live in production Can operate independently and take full ownership of ML products Blends deep technical skill with product thinking and business awareness Skills: data visualization,node.js,feature engineering,keras,python,flask,pandas,docker,rest apis,data,tensorflow,machine learning,express,linux,full stack development,big data handling,react,fastapi,numpy,mongodb,opencv,models,scikit-learn Show more Show less

Location: Thiruvananthapuram, Kerala Job Type: Full-time, On-site Job Required Skills & Qualifications: 6+ years of experience in Python development, specializing in AI-driven applications . Strong expertise in FastAPI for high-performance backend development. Experience working with LLMs (GPT, Llama, Claude, etc.) and AI model deployment. Hands-on experience with LangChain for AI-driven workflows. Experience with vector databases (FAISS, Pine cone, Weaviate, ChromaDB, etc.) . Knowledge of RESTful APIs, GraphQL, and authentication mechanisms . Familiarity with Hugging Face, OpenAI APIs, and fine-tuning LLMs . Experience in asynchronous programming, multiprocessing, and performance tuning . Strong problem-solving skills, debugging expertise, and experience in Agile/Scrum methodologies Key Responsibilities: AI Model Integration: Develop and integrate LLMs into the WayVida platform using LangChain . Backend Development: Design, develop, and optimize scalable FastAPI services for AI-driven applications. API Development & Optimization: Build and maintain high-performance APIs to support AI-based functionalities. Data Processing & Pipelines: Work with large-scale datasets for training and fine-tuning LLMs. Performance Optimization: Improve system efficiency, response times, and model inference speeds. Collaboration with AI & Product Teams: Work with data scientists and engineers to deploy AI solutions effectively. Security & Compliance: Implement best practices for secure API design, data privacy, and compliance . Testing & Code Quality: Ensure high-quality, maintainable, and well-documented code following CI/CD best practices. . Preferred Qualifications: Experience in AI-driven EdTech platforms . Knowledge of retrieval-augmented generation (RAG) and prompt engineering . Familiarity with Docker, Kubernetes , and cloud deployment (Azure, AWS, GCP) . Exposure to MLOps, model versioning, and continuous AI deployments . Show more Show less

Job Title: DevOps Engineer – AI/ML Infrastructure Location: Meril Healthcare Pvt. Ltd, IITM research park, Chennai, Parent company – Meril (https://www.merillife.com/) . Shift: General shift - Monday to Saturday (9.30 am to 6.00 pm). Summary We are seeking a skilled DevOps Engineer with expertise in managing cloud-based AI/ML infrastructure, automation, CI/CD pipelines, and containerized deployments. The ideal candidate will work on AWS-based AI model deployment , database management , API integrations , and scalable infrastructure for AI inference workloads. Experience in ML model serving (MLflow, TensorFlow Serving, Triton Inference Server, BentoML) and on- prem/cloud DevOps will be highly valued. Key Responsibilities Cloud s Infrastructure Management Manage and optimize cloud infrastructure on AWS (SageMaker, EC2, Lambda, RDS, DynamoDB, S3, CloudFormation) . Design, implement, and maintain highly available, scalable AI/ML model deployment pipelines . Set up Infrastructure as Code (IaC) using Terraform, CloudFormation, or Ansible . CI/CD s Automation Develop and manage CI/CD pipelines using GitLabCI/CD, Jenkins, and AWS CodeBuild . Automate deployment of AI models and applications using Docker, Kubernetes (EKS) . Write automation scripts in Bash, Python, or PowerShell for system tasks. APIs AI Model Deployment Deploy and manage Flask/FastAPI-based APIs for AI inference. Optimize ML model serving using MLflow, TensorFlow Serving, Triton Inference Server, and BentoML . Implement monitoring for AI workloads to ensure inference reliability and performance. Security, Monitoring s Logging Implement AWS security best practices (IAM, VPC,Security Groups, Access Controls) . Monitor infrastructure using Prometheus, Grafana, CloudWatch, or ELK Stack . Set up backup and disaster recovery strategies for databases, storage, and models . Database s Storage Management Maintain and optimize MySQL (RDS) and MongoDB (DynamoDB) databases . Handle structured (RDS) and unstructured (S3, DynamoDB) AI data storage . Improve data synchronization between AI models, applications, and web services . On-Prem s Hybrid Cloud Integration (Optional) Manage on-prem AI workloads with GPU acceleration . Optimize AI workloads across cloud and edge devices . Required Skills and Qualifications 3 to 5 years of experience in DevOps, Cloud Infrastructure, or AI/ML Ops . Expertise in AWS (SageMaker, EC2, Lambda, RDS, DynamoDB, S3) . Experience with Docker s Kubernetes (EKS) for container orchestration. Proficiency in CI/CD tools (Jenkins, GitLab CI/CD, AWS CodeBuild) . Strong scripting skills in Bash, Python, or PowerShell . Knowledge of Linux ecosystem (Ubuntu, RHEL, CentOS) . Hands-on experience with ML model deployment (MLflow, TensorFlow Serving, Triton, BentoML) . Strong understanding of networking, security, and monitoring . Experience with database management (MySQL, PostgreSQL, MongoDB) . Preferred Skills AWS Certified DevOps Engineer, CKA (Kubernetes), or Terraform certification . Experience with hybrid cloud (AWS + on-prem GPU servers) . Knowledge of edge AI deployment and real-time AI inference optimization . Interested , Please share your resume to priyadharshini.sridhar@merillife.com Show more Show less

Location: Remote Duration: 3–6 months (Extendable) Stipend: ₹10K–₹20K/month (Based on experience & performance) Start Date: Immediate Reports to: CEO (Directly) About MyMirro At MyMirro, we’re building the future of personalized fashion styling. Our vision is to become India’s smartest personal stylist, powered by AI that deeply understands fashion, body types, cultures, and trends. We've built a proprietary 4-step recommendation engine using multimodal models, deep search, and real-time outfit scoring. We're looking for a smart, technical intern who loves fashion, AI, and solving hard personalization problems. What You'll Work On Maintain and scale our current 4-phase fashion recommendation engine: Product image captioning using LLaVA on RunPod Semantic search using FAISS + SentenceTransformers Outfit scoring engine using style, body shape, trend, and cultural metrics Similar product/outfit discovery APIs Gradually take ownership of: Improving outfit generation logic Optimizing FAISS indexing and embedding pipelines Running evaluations and style consistency checks Experimenting with new models (e.g., DeepSeek R1, FashionCLIP, LaViLa) Building pipelines for user feedback–driven personalization Skills Required Must-Have: 🧠 Strong Python programming experience 🤖 Exposure to ML / deep learning (transformers, huggingface, or vision-language models) 🔍 Knowledge of FAISS or any vector search engine 🧾 Comfortable with APIs, JSON, and working with structured/unstructured data 👕 Passion for fashion tech, recommendation systems, or personalization 💬 Good communication — you'll work directly with the CEO and think out loud Bonus: 📊 Experience with SentenceTransformers, OpenAI, or multimodal LLMs 🎨 Familiarity with fashion data, body types, style trends 🔁 Experience with vector databases (Pinecone, Weaviate, Qdrant, etc.) ⚡ Familiarity with tools like RunPod, HuggingFace Spaces, or Docker 🧠 Knowledge of embeddings, outfit scoring, or recommender systems 🧵 Interest in working at the intersection of fashion + AI What You’ll Gain Real-world experience working on a production-level AI recommendation system Direct mentorship from the founder/CEO Opportunity to drive core technical decisions in a fast-growing startup Experience in fashion-tech, one of the fastest growing sectors Exposure to the full ML pipeline: inference, retrieval, scoring, evaluation Letter of recommendation + potential PPO for outstanding candidates How to Apply Send us at mayank.lakhani@mymirro.in: Your CV / LinkedIn / GitHub (Optional) Any projects related to recommendation engines, AI/ML, or fashion A short paragraph on why you’re excited about this role Show more Show less

Company Overview Pinnacle Infotech values inclusive growth in an agile, diverse environment. With 30+ years of global experience, 3,400+ experts completed 15,000+ projects across 43+ countries for 5,000+ clients. Join us for rapid advancement, cutting-edge training, and impactful global projects. Embrace E.A.R.T.H. values, celebrate uniqueness, and drive swift career growth with Pinnaclites! Position Name : Data Scientist (Computer Vision Engineer) Years of Experience : 2-4 years Location - Madurai, Tamil Nadu Qualification - B.Tech/B.E/Any Master Degree(CS,IT) or Any MBA No. of open Position - 1 Primary Skills: Expected Years of Exp Work with large-scale image and video datasets to extract actionable insights and automate visual tasks. 2-4 yrs Collaborate with cross-functional teams (ML engineers, product managers, designers) to integrate vision models into production pipelines. 2-4 yrs Design, implement, and optimize computer vision algorithms for tasks such as object detection, image classification, tracking & segmentation. 2-4 yrs Design and run tests, experiments, and data analysis to support product and business decisions. 2-4 yrs Job Responsibilities : Design and train machine learning like Object detection, Image classification, Face recognition, OCR (optical character recognition). Data Management and Preprocessing. Image & Video Data Analysis. Data Annotation & Augmentation. Work with streaming data for real-time inference. Apply techniques to improve model generalization. Innovate algorithms to solve domain-specific problems. Interested candidates, kindly share your resume at sunitas@pinnacleinfotech.com Show more Show less

Techvantage.ai is a next-generation technology and product engineering company at the forefront of innovation in Generative AI, Agentic AI , and autonomous intelligent systems . We design intelligent platforms that solve complex business problems and deliver measurable impact through cutting-edge AI technologies. Role Overview: We are seeking an experienced Solution Architect with a strong foundation in software architecture and a working knowledge of AI-based products or platforms . In this role, you will be responsible for designing robust, scalable, and secure architectures that support AI-driven applications and enterprise systems. You will work closely with cross-functional teams—including data scientists, product managers, and engineering leads—to bridge the gap between business needs, technical feasibility, and AI capability. What we are looking from an ideal candidate? Architect end-to-end solutions for enterprise and product-driven platforms, including components such as data pipelines, APIs, AI model integration, cloud infrastructure, and user interfaces. Guide teams in selecting the right technologies, tools, and design patterns to build scalable systems. Collaborate with AI/ML teams to understand model requirements and ensure smooth deployment and integration into production. Define system architecture diagrams, data flow, service orchestration, and infrastructure provisioning using modern tools. Work closely with stakeholders to translate business needs into technical solutions, with a focus on scalability, performance, and security. Provide leadership on best practices for software development, DevOps, and cloud-native architecture. Conduct architecture reviews and ensure alignment with security, compliance, and performance standards. Preferred Skills: What skills do you need? Requirements: 10+ years of experience in software architecture or solution design roles. Proven experience designing systems using microservices , RESTful APIs , event-driven architecture , and cloud-native technologies. Hands-on experience with at least one major cloud provider: AWS , GCP , or Azure . Familiarity with AI/ML platforms or components , such as integrating AI models, MLOps pipelines, or inference services. Understanding of data architectures, including data lakes , streaming , and ETL pipelines. Strong experience with containerization ( Docker , Kubernetes ) and DevOps principles. Ability to lead technical discussions, make design trade-offs, and communicate with both technical and non-technical stakeholders. Preferred Qualifications: Exposure to AI model lifecycle management , prompt engineering , or real-time inference workflows. Experience with infrastructure-as-code (Terraform, Pulumi). Knowledge of GraphQL, gRPC, or serverless architectures. Previous experience working in AI-driven product companies or digital transformation programs. What We Offer: High-impact role in designing intelligent systems that shape the future of AI adoption Work with forward-thinking engineers, researchers, and innovators Strong focus on career growth, learning, and technical leadership Compensation is not a constraint for the right candidate

Techvantage.ai is a next-generation technology and product engineering company at the forefront of innovation in Generative AI, Agentic AI , and autonomous intelligent systems . We build intelligent, cutting-edge solutions designed to scale and evolve with the future of artificial intelligence. Role Overview: We are looking for a skilled and versatile AI Infrastructure Engineer (DevOps/MLOps) to build and manage the cloud infrastructure, deployment pipelines, and machine learning operations behind our AI-powered products. You will work at the intersection of software engineering, ML, and cloud architecture to ensure that our models and systems are scalable, reliable, and production-ready. What we are looking from an ideal candidate? Design and manage CI/CD pipelines for both software applications and machine learning workflows. Deploy and monitor ML models in production using tools like MLflow, SageMaker, Vertex AI, or similar. Automate the provisioning and configuration of infrastructure using IaC tools (Terraform, Pulumi, etc.). Build robust monitoring, logging, and alerting systems for AI applications. Manage containerized services with Docker and orchestration platforms like Kubernetes . Collaborate with data scientists and ML engineers to streamline model experimentation, versioning, and deployment. Optimize compute resources and storage costs across cloud environments (AWS, GCP, or Azure). Ensure system reliability, scalability, and security across all environments. Preferred Skills: What skills do you need? 5+ years of experience in DevOps, MLOps , or infrastructure engineering roles. Hands-on experience with cloud platforms ( AWS, GCP, or Azure ) and services related to ML workloads. Strong knowledge of CI/CD tools (e.g., GitHub Actions, Jenkins, GitLab CI). Proficiency in Docker , Kubernetes , and infrastructure-as-code frameworks. Experience with ML pipelines , model versioning, and ML monitoring tools. Scripting skills in Python , Bash , or similar for automation tasks. Familiarity with monitoring/logging tools (Prometheus, Grafana, ELK, CloudWatch, etc.). Understanding of ML lifecycle management and reproducibility. Preferred Qualifications: Experience with Kubeflow , MLflow , DVC , or Triton Inference Server . Exposure to data versioning , feature stores , and model registries . Certification in AWS/GCP DevOps or Machine Learning Engineering is a plus. Background in software engineering, data engineering, or ML research is a bonus. What We Offer: Work on cutting-edge AI platforms and infrastructure Cross-functional collaboration with top ML, research, and product teams Competitive compensation package – no constraints for the right candidate

Senior Software Engineer Bangalore, Karnataka, India Date posted Jun 09, 2025 Job number 1822812 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 Join our team building the foundational infrastructure that ensures safety, compliance, and integrity at global scale. As a Senior Software Engineer on the Trust & Safety Platform team, you’ll design and build the core, low-latency systems that evaluate ads, content, and user signals against policy in real time. These systems process hundreds of billions of entities daily, providing the enforcement backbone for content moderation, ad quality, and user protection workflows across Microsoft’s ecosystem. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Qualifications Required Qualifications: Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. 4+ years of experience building distributed systems or high-scale backend infrastructure. Strong programming experience in C++, C# with knowledge of object-oriented design, concurrency, and system architecture. Expertise in performance optimization, latency tuning, and scalable service design. Experience with stream processing or event-driven architectures (e.g., Apache Flink, Kafka Streams, Beam). Experience with cloud-native data infrastructure (e.g., Kubernetes, Azure, BigQuery, Delta Lake, Cosmos DB). Other Requirements: 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. Preferred Qualifications: Building efficient ML inference flow into production at scale. #MicrosoftAI Responsibilities Design and implement distributed, real-time pipelines that operate with high throughput and low latency, handling spiky and dynamic workloads across the globe. Build core platform components including rule execution engines, signal aggregators, and policy enforcement APIs that support human and automated decisions. Collaborate with ML engineers to support scalable inference integration while keeping systems modular, performant, and cost-efficient. Drive system-level improvements in observability, fault tolerance, and scalability. Lead technical design reviews, own key service components, and contribute to long-term architecture and platform evolution. 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.

Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com. Job Description Role Purpose Job Description / Roles & Responsibilities (in Detail) Strong understanding of machine learning and deep learning principles and algorithms. Experience in developing and implementing generative AI models and algorithms. Proficiency in programming languages such as Python, TensorFlow, and PyTorch. Ability to work with large datasets and knowledge of data preprocessing techniques. Familiarity with natural language processing (NLP) and computer vision for generative AI applications. Experience in building and deploying generative AI systems in real-world applications. Utilize advanced machine learning techniques to develop and train generative AI models. Collaborate with cross-functional teams to groom and preprocess large datasets for model training. Research and implement cutting-edge algorithms and architectures for generative AI applications. Optimize model performance and scalability for real-time inference and deployment. Stay current with industry trends and advancements in generative AI technology to drive innovation. Experiment with different hyperparameters and model configurations to improve generative AI model quality. Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation, Choose suitable DL algorithms, software, hardware and suggest integration methods. Ensure AI ML solutions are developed, and validations are performed in accordance with Responsible AI guidelines & Standards To closely monitor the Model Performance and ensure Model Improvements are done post Project Delivery Provide technical expertise and guidance to support the integration of generative AI solutions into various products and services. Coach and mentor our team as we build scalable machine learning solutions Strong communication skills and an easy-going attitude Oversee development and implementation of assigned programs and guide teammates Carry out testing procedures to ensure systems are running smoothly ork abilities to collaborate with cross-functional teams. Proven track record of delivering innovative solutions using generative AI technologies. Ability to stay updated with the latest advancements in generative AI and adapt to new techniques and methodologies. ͏ Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention. Come to Wipro. Realize your ambitions. Applications from people with disabilities are explicitly welcome.

A - 1 JOB CONTENT To aid business in their decision making using qualitative, quantitative analysis & automation. Required to perform optimization or statistical methods & interpret findings for taking business decisions. Take up Automation & AI projects for the organisation to improve productivity and expedite decisions. Drive the Digital transformation initiatives and work on Plant IT/OT analytics A - 2 KEY RESPONSIBILITIES 1. Work closely with businesses and executives to propose, develop, implement, test, and evaluate digital and data-based solutions 2. Develop predictive algorithms that analyze data and recommend data-driven solutions 3. Drive data-driven decision-making by gathering, analyzing, and disseminating business insights 4. Develop research and analytical methods for forecasting, modelling, and optimizing operations 5. Conduct data mining, predictive analytics, and ad hoc analysis using R, Python, SQL, Qlik, and other business intelligence software 6. Provide ongoing mentorship and coaching to data science team & maintain the company's data science capabilities by regulary having sessions with the business on possibilities 7. Be conversant with AI technologies for use internally -- for example, conversational AI systems, AI-driven robots, other autonomous machines 8. Ability to manage a team of Data Scientisit, Data Engineers and Developers 9. Adept in machine learning, staistical analysis, approaches for solving business problems such as classification, clustering, regression, statistical inference, anomaly detection, collaborative filtering, natural language processing, experimental design and social networking analysis 10. Work on disruptive technologies such AI, IOT, blockchain, VR/AR etc and harness its potential for enabling businesses to meet their objectives either on cost or revenue side A - 3 QUALIFICATIONS ESSENTIAL BE & Post Graduation in Data Science/Analytics or MS in Statistics/Computer Engineering/Data Science A - 4 EXPERIENCE : ESSENTIAL Experience in using statistical/ data science computer languages (Python & R) & basic SQL - very good programmable skills Knowledge of ML techniques, Deep learning & AI/ Gen AI alogrithims (CART, ANN, NLP, GNN etc) Knowledge of advanced statistical techniques & its application Having worked on various Data Science tool -MS Azure or Amazon Sage maker Exposure to AI, Automation & IOT/Plant IT/OT will be an added advantage Experience: 10+ years in Data Scientists or Analytics function Qualification: MS/ Msc Statistics Job Types: Full-time, Permanent Pay: Up to ₹3,000,000.00 per year Benefits: Provident Fund Schedule: Day shift Work Location: In person

We is looking for a skilled Machine Learning Engineer with hands-on experience deploying models on Google Cloud Platform (GCP) using Vertex AI. This role involves enabling real-time and batch model inferencing based on specific business requirements, with a strong focus on production-grade ML deployments. Experience: 3 to 4 years Key Responsibilities: * Deploy machine learning models on GCP using Vertex AI. * Design and implement real-time and batch inference pipelines. * Monitor model performance, detect drift, and manage lifecycle. * Ensure adherence to model governance best practices and support ML-Ops workflows. * Collaborate with cross-functional teams to support Credit Risk, Marketing, and Customer Service use cases, especially within the retail banking domain. * Develop scalable and maintainable code in Python and SQL. * Work with diverse datasets, perform feature engineering, and build, train, and fine-tune advanced predictive models. * Contribute to model deployment in the lending space. Required Skills & Experience: * Strong expertise in Python and SQL. * Proficient with ML libraries and frameworks such as scikit-learn, pandas, NumPy, spaCy, CatBoost, etc. * In-depth knowledge of GCP Vertex AI and ML pipeline orchestration. * Experience with ML-Ops and model governance. * Exposure to use cases in retail banking—Credit Risk, Marketing, and Customer Service. * Experience working with structured and unstructured data. Nice to Have: * Prior experience deploying models in the lending domain. * Understanding of regulatory considerations in financial services. Job Type: Full-time Schedule: Day shift Work Location: In person

Our Company Techvantage.ai is a next-generation technology and product engineering company at the forefront of innovation in Generative AI, Agentic AI , and autonomous intelligent systems . We design intelligent platforms that solve complex business problems and deliver measurable impact through cutting-edge AI technologies. Role Overview We are seeking an experienced Solution Architect with a strong foundation in software architecture and a working knowledge of AI-based products or platforms . In this role, you will be responsible for designing robust, scalable, and secure architectures that support AI-driven applications and enterprise systems. You will work closely with cross-functional teams—including data scientists, product managers, and engineering leads—to bridge the gap between business needs, technical feasibility, and AI capability. What we are looking from an ideal candidate? Architect end-to-end solutions for enterprise and product-driven platforms, including components such as data pipelines, APIs, AI model integration, cloud infrastructure, and user interfaces. Guide teams in selecting the right technologies, tools, and design patterns to build scalable systems. Collaborate with AI/ML teams to understand model requirements and ensure smooth deployment and integration into production. Define system architecture diagrams, data flow, service orchestration, and infrastructure provisioning using modern tools. Work closely with stakeholders to translate business needs into technical solutions, with a focus on scalability, performance, and security. Provide leadership on best practices for software development, DevOps, and cloud-native architecture. Conduct architecture reviews and ensure alignment with security, compliance, and performance standards. Preferred Skills What skills do you need? Requirements 10+ years of experience in software architecture or solution design roles. Proven experience designing systems using microservices, RESTful APIs, event-driven architecture, and cloud-native technologies. Hands-on experience with at least one major cloud provider: AWS, GCP, or Azure. Familiarity with AI/ML platforms or components, such as integrating AI models, MLOps pipelines, or inference services. Understanding of data architectures, including data lakes, streaming, and ETL pipelines. Strong experience with containerization (Docker, Kubernetes) and DevOps principles. Ability to lead technical discussions, make design trade-offs, and communicate with both technical and non-technical stakeholders. Preferred Qualifications Exposure to AI model lifecycle management, prompt engineering, or real-time inference workflows. Experience with infrastructure-as-code (Terraform, Pulumi). Knowledge of GraphQL, gRPC, or serverless architectures. Previous experience working in AI-driven product companies or digital transformation programs. What We Offer High-impact role in designing intelligent systems that shape the future of AI adoption Work with forward-thinking engineers, researchers, and innovators Strong focus on career growth, learning, and technical leadership Compensation is not a constraint for the right candidate Show more Show less

Join our team building the foundational infrastructure that ensures safety, compliance, and integrity at global scale. As a Senior Software Engineer on the Trust & Safety Platform team, you’ll design and build the core, low-latency systems that evaluate ads, content, and user signals against policy in real time. These systems process hundreds of billions of entities daily, providing the enforcement backbone for content moderation, ad quality, and user protection workflows across Microsoft’s ecosystem. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Responsibilities Design and implement distributed, real-time pipelines that operate with high throughput and low latency, handling spiky and dynamic workloads across the globe. Build core platform components including rule execution engines, signal aggregators, and policy enforcement APIs that support human and automated decisions. Collaborate with ML engineers to support scalable inference integration while keeping systems modular, performant, and cost-efficient. Drive system-level improvements in observability, fault tolerance, and scalability. Lead technical design reviews, own key service components, and contribute to long-term architecture and platform evolution. Qualifications Required Qualifications: Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. 4+ years of experience building distributed systems or high-scale backend infrastructure. Strong programming experience in C++, C# with knowledge of object-oriented design, concurrency, and system architecture. Expertise in performance optimization, latency tuning, and scalable service design. Experience with stream processing or event-driven architectures (e.g., Apache Flink, Kafka Streams, Beam). Experience with cloud-native data infrastructure (e.g., Kubernetes, Azure, BigQuery, Delta Lake, Cosmos DB). Other Requirements 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. Preferred Qualifications Building efficient ML inference flow into production at scale. #MicrosoftAI Microsoft is an equal opportunity employer. Consistent with applicable law, 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. Show more Show less

Position Title: AI/ML Engineer Company : Cyfuture India Pvt. Ltd. Industry : IT Services and IT Consulting Location : Sector 81, NSEZ, Noida (5 Days Work From Office) Website : www.cyfuture.com About Cyfuture Cyfuture is a trusted name in IT services and cloud infrastructure, offering state-of-the-art data center solutions and managed services across platforms like AWS, Azure, and VMWare. We are expanding rapidly in system integration and managed services, building strong alliances with global OEMs like VMWare, AWS, Azure, HP, Dell, Lenovo, and Palo Alto. Position Overview We are hiring an experienced AI/ML Engineer to lead and shape our AI/ML initiatives. The ideal candidate will have hands-on experience in machine learning and artificial intelligence, with strong leadership capabilities and a passion for delivering production-ready solutions. This role involves end-to-end ownership of AI/ML projects, from strategy development to deployment and optimization of large-scale systems. Key Responsibilities Lead and mentor a high-performing AI/ML team. Design and execute AI/ML strategies aligned with business goals. Collaborate with product and engineering teams to identify impactful AI opportunities. Build, train, fine-tune, and deploy ML models in production environments. Manage operations of LLMs and other AI models using modern cloud and MLOps tools. Implement scalable and automated ML pipelines (e.g., with Kubeflow or MLRun). Handle containerization and orchestration using Docker and Kubernetes. Optimize GPU/TPU resources for training and inference tasks. Develop efficient RAG pipelines with low latency and high retrieval accuracy. Automate CI/CD workflows for continuous integration and delivery of ML systems. Key Skills & Expertise 1. Cloud Computing & Deployment Proficiency in AWS, Google Cloud, or Azure for scalable model deployment. Familiarity with cloud-native services like AWS SageMaker, Google Vertex AI, or Azure ML. Expertise in Docker and Kubernetes for containerized deployments Experience with Infrastructure as Code (IaC) using tools like Terraform or CloudFormation. 2. Machine Learning & Deep Learning Strong command of frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost. Experience with MLOps tools for integration, monitoring, and automation. Expertise in pre-trained models, transfer learning, and designing custom architectures. 3. Programming & Software Engineering Strong skills in Python (NumPy, Pandas, Matplotlib, SciPy) for ML development. Backend/API development with FastAPI, Flask, or Django. Database handling with SQL and NoSQL (PostgreSQL, MongoDB, BigQuery). Familiarity with CI/CD pipelines (GitHub Actions, Jenkins). 4. Scalable AI Systems Proven ability to build AI-driven applications at scale. Handle large datasets, high-throughput requests, and real-time inference. Knowledge of distributed computing: Apache Spark, Dask, Ray. 5. Model Monitoring & Optimization Hands-on with model compression, quantization, and pruning. A/B testing and performance tracking in production. Knowledge of model retraining pipelines for continuous learning. 6. Resource Optimization Efficient use of compute resources: GPUs, TPUs, CPUs. Experience with serverless architectures to reduce cost. Auto-scaling and load balancing for high-traffic systems. 7. Problem-Solving & Collaboration Translate complex ML models into user-friendly applications. Work effectively with data scientists, engineers, and product teams. Write clear technical documentation and architecture reports. Show more Show less

Uber Eats is seeking a highly skilled and motivated Staff Data Scientist to join our Search Team. In this role, you will be a key driver in enhancing the search experience for millions of users across the globe. You'll bring deep statistical expertise to guide decision-making, improve product performance, and ensure our evaluations and insights are rooted in methodological rigor. What You'll Do Conduct robust statistical analyses on complex datasets to identify product opportunities, shape roadmap priorities, and optimize user experiences in search. Design and evaluate A/B tests and quasi-experiments, applying best practices in experimental methodology to ensure high-quality, unbiased insights. Build and maintain statistical frameworks for defining and measuring ground truth - identifying reliable signals to evaluate search relevance, personalization, and user satisfaction. Apply advanced sampling strategies to construct representative datasets for both offline and online evaluation pipelines, ensuring scalability and statistical power. Develop rigorous evaluation metrics that reflect real-world product performance and align closely with user and business goals. Lead initiatives to strengthen causal inference practices across the team, applying methods like matching, regression discontinuity, and difference-in-differences where appropriate. Partner with product managers, engineers, and other scientists to translate open-ended product questions into structured analytical approaches. Provide mentorship and technical leadership to other scientists, promoting a culture of statistical excellence and continuous learning. What You'll Need: M.S. or Bachelor's degree in Statistics, Economics, Mathematics, Operations Research, Computer Science, or a related quantitative field. 10+ years of industry experience in data science or applied analytics, ideally with experience in consumer products, search, or recommendation systems. Deep expertise in ground truth design, and evaluation methodologies for complex user-facing systems. Proven experience with statistical sampling techniques and working with offline evaluation pipelines to assess models and product performance. Strong fluency in experimentation design, causal inference, and observational data analysis. Proficiency with tools like SQL, Python, and R for data manipulation, modeling, and visualization. Excellent communication skills - able to present statistical findings clearly and influence product and engineering decisions through data. A strong product sense and the ability to balance analytical rigor with practical business impact. Show more Show less

Summary -Explore, develop, implement and evaluate Digital innovation solutions that address customer needs. Co-create with key stakeholders to build partnerships and collaborations -Leads the delivery of multiple projects across a variety of creative and marketing channels, including print and digital media. Develop and coordinate project plans across the design, development and production stages of a project to support the successful delivery within set KPI's. -Works in collaboration with brand teams, technical teams and all functions to maximize value. -Provides consultancy, advice and assistance on strategy for commercialization of products, and influence marketing/Marketing Sales Operation team on decision making on Sales Force resource allocation in most optimal ways, through delivery of proven analytics based projects. -Provide analytics support to Novartis internal customers About The Role Job Description Position Title : Manager Dada Science Location – Hyd-India Hybrid About The Role Provide analytics support to Novartis internal customers (CPOs & Regional marketing and sales teams) on various projects. Support and facilitate data enabled decision making internal customers using data analysis and data science techniques/methods on internal and external(3rd party) data to solve business problems Team NBS CONEXTS-I&CS business support in building capabilities by involving in various initiatives like knowledge sharing, on-boarding and training support, support in all business related tasks/activities, building process documentation and knowledge repositories Your responsibilities include but are not limited to Delivering projects and leading internal customer expectations across multi-channel marketing analytics, Portfolio Analytics, Targeting and Segmentation, Predictive Analytics, Prioritisation and Optimization Build and deliver customer requirements as per agreed SLAs (timeliness, accuracy, quality, etc.) and drive excellent customer happiness. Deliver sophisticated analytical and statistical solutions for various projects related to promotion evaluation, multi-channel marketing (MCM) campaign design, return on investment (value) analysis, resource allocation, segmentation, targeting, and other ad-hoc business questions Support exploratory research to identify new areas of application of advanced analytics/data science in providing improved decision-making support. Deliver services through structured project management approach with appropriate documentation and communication throughout the delivery of services. Automation of project codes and development of front-end delivery solutions. Support in creation and maintenance of standard operating procedures (SOPs), quality checklists that will enable excellent quality outputs within the function. Support team leaders in recruitment and on-boarding of new associates within the organization. Participate in various knowledge sharing sessions that enables growth and improves quality of NBS CONEXTS deliverables across the function. Align with all internal functional operating procedures like time tracking, critical metric tracking and reporting, and other internal systems and processes. Comply to all Novartis operating procedures as per legal/IT/HR requirements. What You’ll Bring To The Role Deriving impactful strategies by defining clear category objectives, working with analytical data, business partners and market expertise. Aligning strategies to measurable target and clearly conveying them to the organization. Should have strong quantitative and systems background. Strong analytical thinking with problem solving approach and good ability to understand new data sources in short timeframe and embed them into standard analyses. Good understanding of pharmaceutical domain and data would be ideal. Strong partner leadership skills and ability to work with multiple partners. Should have worked in an international/Global company with exposure to working in cross-cultural environment. Strong and proactive business results-focus, and proven track record to provide insights that increase efficiency. Hands on to Classification (CART, RF, SVM, GBM, etc.) Clustering, Design of Experiments, Monte Carlo Simulations, Statistical Inference, Feature Engineering, Time Series Forecasting o Good to have: Stochastic models, Bayesian Models, Markov Chains, Dynamic Programming and Optimization Hands on to Project Management, Solid understanding of MS-Office (MS Excel, VBA, PowerPoint, Access), Learning agility, Pharmaceutical industry domain/datasets knowledge – desirable Desirable Requirements University/Advanced degree in Statistics, Economics, Mathematics, Computer Science, Bioinformatics, Ops Research, is preferable. Min 6+ years of hands-on experience in analytics in marketing analytics and experience in pharma industry is preferable. Statistical Modeling/Machine Learning techniques like Regression (esp, GLM, non-linear, etc.). experience in any one of R or Python and exposure to SAS and SQL. Familiarity with Alteryx will be a bonus. Visualization tools – Qlikview, Qliksense, Tableau. Why Novartis Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us! Learn more here: https://www.novartis.com/about/strategy/people-and-culture You’ll receive: You can find everything you need to know about our benefits and rewards in the Novartis Life Handbook. https://www.novartis.com/careers/benefits-rewards Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, Join the Novartis Network here: https://talentnetwork.novartis.com/network. Commitment To Diversity & Inclusion Novartis embraces diversity, equal opportunity, and inclusion. We are committed to building diverse teams, representative of the patients and communities we serve, and we strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture Join our Novartis Network: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up: https://talentnetwork.novartis.com/network Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards Show more Show less

Role: Consultant - Generative AI Location: Gurgaon We are seeking a highly skilled Generative AI Engineer to join the team. The Generative AI Engineer will play a pivotal role in designing, coding, and deploying advanced AI solutions using state-of-the-art technologies such as Databricks, AI Fabric, Azure, and Snowflake. This role requires a deep understanding of AI/ML frameworks and cloud-based environments, focusing on building scalable, high-performance AI solutions that drive value for global network. Key responsibilities include: 1. AI Solution Development: • Design, develop, and deploy Generative AI models and solutions that address complex business challenges across advisory, tax, and audit services. • Leverage platforms such as Databricks for data engineering and AI model development, AI Fabric for orchestration and deployment, and Snowflake for scalable data management. •Utilize Azure cloud services to implement and scale AI solutions, ensuring high availability, performance, and security. 2. Technical Leadership and Collaboration : • Collaborate with data scientists, AI architects, and software engineers to define technical requirements and develop end-to-end AI solutions. • Lead the development of AI models from experimentation and prototyping through to production, ensuring alignment with business objectives. • Work closely with cross-functional teams to integrate AI solutions into existing workflows and systems, optimizing for efficiency and usability. 3. Coding and Implementation: • Write high-quality, maintainable code using Python, Scala, or similar programming languages, focusing on AI/ML libraries and frameworks. • Develop and optimize data pipelines using Databricks, ensuring seamless data flow from ingestion to AI model training and inference. • Implement AI solutions using AI Fabric, focusing on model orchestration, deployment, and monitoring within a cloud environment. 4. Data Management and Integration: • Design and manage data architectures using Snowflake, ensuring data is organized, accessible, and secure for AI model training and deployment. • Integrate data from various sources, transforming and preparing it for AI model development, ensuring data quality and integrity. • Work with large datasets, applying best practices for data engineering, ETL processes, and real-time data processing 5. Cloud & Infrastructure Management: • Deploy AI models and services in Azure, utilizing cloud-native tools and best practices to ensure scalability, reliability, and security. • Implement CI/CD pipelines to automate the deployment and management of AI models, ensuring rapid iteration and continuous delivery. • Optimize infrastructure for AI workloads, balancing performance, cost, and resource utilization. 6. Performance Tuning and Optimization: • Continuously monitor and optimize AI models and data pipelines to improve performance, accuracy, and scalability. • Implement strategies for model fine-tuning, hyperparameter optimization, and feature engineering to enhance AI solution effectiveness. • Troubleshoot and resolve technical issues related to AI model deployment, data processing, and cloud infrastructure. 7. Innovation and Continuous Improvement: • Stay updated with the latest advancements in Gen AI, cloud computing, and big data technologies, applying new techniques to improve solutions. • Experiment with emerging technologies and frameworks to drive innovation. • Contribute to the development of AI best practices, coding standards, and technical documentation to ensure consistency and quality across projects Experience Required: 2+ years of experience in AI, Machine Learning, or related fields, with hands-on experience in developing and deploying AI solutions. • Proven experience with AI frameworks such as TensorFlow, PyTorch, and experience in working with Databricks, AI Fabric, and Snowflake. • Extensive experience with Azure cloud services, including AI and data services, and a strong background in cloud-native development. • Expertise in coding with Python, Scala, or similar languages, with a focus on AI/ML libraries and big data processing. Proficiency in designing and coding AI models, data pipelines, and cloud-based solutions. • Strong understanding of AI/ML algorithms, data engineering, and model deployment strategies. • Experience with cloud infrastructure management, particularly in Azure, and the ability to optimize AI workloads for performance and cost. • Excellent problem-solving skills and the ability to work collaboratively in a cross-functional team environment. • Strong communication skills, with the ability to articulate complex technical concepts to technical and non-technical stakeholders. Please share your resume at shikha@tdnewton.com Show more Show less

Who We Are Balbix is the world's leading platform for cybersecurity posture automation. Using Balbix, organizations can discover, prioritize and mitigate unseen risks and vulnerabilities at high velocity. With seamless data collection and petabyte-scale analysis capabilities, Balbix is deployed and operational within hours, and helps to decrease breach risk immediately. Balbix counts many global 1000 companies among its rapidly growing customer base . We are backed by John Chambers (the former CEO and Chairman of Cisco) , top Silicon Valley VCs and global investors . We have been called magical , and have received raving reviews as well as customer testimonials , numerous industry awards , and recognition by Gartner as a Cool Vendor , and by Frost & Sullivan . DATA SCIENCE AT BALBIX At Balbix we believe in using the right algorithms and tools to ensure correctness, performance and deliver an excellent user experience. We draw boldly from the latest in AI/ML research but are unafraid to go beyond Bayesian inference and statistical models if the situation demands it. We are generalists, caring as much about storytelling with data, as about bleeding edge techniques, scalable model training and deployment. We are building a data science culture with equal emphasis on knowing our data, grokking security-first principles, caring about customer needs, explaining our model predictions, deploying at scale, communicating our work, and adapting the latest advances. We look out for each other, enjoy each others’ company, and keep an open channel of communication about all things data and non-data. This role is open for Bengaluru/Gurugran. You Will Design and develop an ensemble of classical and deep learning algorithms for modeling complex interactions between people, software, infrastructure and policies in an enterprise environment Design and implement algorithms for statistical modeling of enterprise cybersecurity risk Apply data-mining, AI and graph analysis techniques to address a variety of problems including modeling, relevance and recommendation Build production quality solutions that balance complexity and performance Participate in the engineering life-cycle at Balbix, including designing high quality ML infrastructure and data pipelines, writing production code, conducting code reviews and working alongside our infrastructure and reliability teams Drive the architecture and the usage of open source software library for numerical computation such as TensorFlow, PyTorch, and ScikitLearn You Are Able to take on very complex problems, learn quickly, iterate, and persevere towards a robust solution Product-focused and passionate about building truly usable systems Collaborative and comfortable working across teams including data engineering, front end, product management, and DevOps Responsible and like to take ownership of challenging problems A good communicator, and facilitate teamwork via good documentation practices Comfortable with ambiguity and thrive in designing algorithms for evolving needs Intuitive in using the right type of models to address different product needs Curious about the world and your profession, constant learner You Have A Ph.D. in Computer Science and Engineering or related field 3+ years of experience in the field of Machine Learning, programming in Python, and building scalable distributed systems Foundational knowledge of probability, statistics and linear algebra Expertise in state-of-the-art AI algorithms such as deep-learning, NLP, probabilistic graphical models, graphical algorithms, reinforcement learning and time-series analysis Knowledge of statistical analysis and modeling techniques, and model explainability Life @ Balbix At Balbix, we have built a culture that aligns to our values of ownership, customer focus, curiosity, tenacity, innovation, judgement, teamwork, communication, honesty and impact. In joining our team you’ll work with very motivated and knowledgeable people, build pioneering products and utilize cutting-edge technology. Our Balbix team members see rapid career growth opportunities stemming from our culture of alignment, bottom up innovation, our clarity of goals and unrelenting mission. Last but not least, developing the world's most advanced platform to address what the most important (and hardest) technology problem facing mankind today is exceptionally rewarding! More information at https://www.balbix.com/company/careers/ Please reach out if you want a seat on our rocket-ship and are passionate about changing the cybersecurity equation. Show more Show less

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 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. 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. 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 Master’s or Ph.D. in a quantitative field such as statistics, economics, industrial engineering and operations research, applied math, or other relevant quantitative field. 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. 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. Show more Show less

Job Responsibilities: Evaluate and source appropriate cloud infrastructure solutions for machine learning needs, ensuring cost-effectiveness and scalability based on project requirements. Automate and manage the deployment of machine learning models into production environments, ensuring version control for models and datasets using tools like Docker and Kubernetes. Set up monitoring tools to track model performance and data drift, conduct regular maintenance, and implement updates for production models. Work closely with data scientists, software engineers, and stakeholders to align on project goals, facilitate knowledge sharing, and communicate findings and updates to cross-functional teams. Design, implement, and maintain scalable ML infrastructure, optimizing cloud and on-premise resources for training and inference. Document ML processes, pipelines, and best practices while preparing reports on model performance, resource utilization, and system issues. Provide training and support for team members on ML Ops tools and methodologies, and stay updated on industry trends and emerging technologies. Diagnose and resolve issues related to model performance, infrastructure, and data quality, implementing solutions to enhance model robustness and reliability. Education, Technical Skills & Other Critical Requirement: 10+ years of relevant experience in AI/ analytics product & solution delivery Bachelor’s/master’s degree in an information technology/computer science/ Engineering or equivalent fields experience. Proficiency in frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong skills in Python and/or R; familiarity with Java, Scala, or Go is a plus. Experience with cloud services such as AWS, Azure, or Google Cloud Platform, particularly in ML services (e.g., AWS SageMaker, Azure ML). CI/CD tools (e.g., Jenkins, GitLab CI), containerization (e.g., Docker), and orchestration (e.g., Kubernetes). Experience with databases (SQL and NoSQL), data pipelines, ETL processes, ML pipeline orchestration (Airflow) Familiarity with monitoring and logging tools such as Prometheus, Grafana, or ELK stack. Proficient in using Git for version control. Strong analytical and troubleshooting abilities to diagnose and resolve issues effectively. Good communication skills for working with cross-functional teams and conveying technical concepts to non-technical stakeholders. Ability to manage multiple projects and prioritize tasks in a fast-paced environment. Show more Show less

🚨 We are Hiring 🚨 https://grhombustech.com/jobs/job-description-senior-test-automation-lead-playwright-ai-ml-focus/ Job Description Job Title: Senior Test Automation Lead – Playwright (AI/ML Focus) Location: Hyderabad Experience: 10 - 12 years Job Type: Full-Time Company Overview: GRhombus Technologies Pvt Ltd, a pioneer in Software Solutions – Especially on Test Automation, Cyber Security, Full Stack Development, DevOps, Salesforce, Performance Testing and Manual Testing. GRhombus delivery centres are located in India at Hyderabad, Chennai, Bengaluru and Pune. In the Middle East, we are located in Dubai. Our partner offices are located in the USA and the Netherlands. About the Role: We are seeking a passionate and technically skilled Senior Test Automation Lead with deep experience in Playwright-based frameworks and a solid understanding of AI/ML-driven applications. In this role, you will lead the automation strategy and quality engineering practices for next-generation AI products that integrate large-scale machine learning models, data pipelines, and dynamic, intelligent UIs. You will define, architect, and implement scalable automation solutions across AI-enhanced features such as recommendation engines, conversational UIs, real-time analytics, and predictive workflows, ensuring both functional correctness and intelligent behavior consistency. Key Responsibilities: Test Automation Framework Design & Implementation Design and implement robust, modular, and extensible Playwright automation frameworks using TypeScript/JavaScript. Define automation design patterns and utilities that can handle complex AI-driven UI behaviors (e.g., dynamic content, personalization, chat interfaces). Implement abstraction layers for easy test data handling, reusable components, and multi-browser/platform execution. AI/ML-Specific Testing Strategy Partner with Data Scientists and ML Engineers to understand model behaviors, inference workflows, and output formats. Develop strategies for testing non-deterministic model outputs (e.g., chat responses, classification labels) using tolerance ranges, confidence intervals, or golden datasets. Design tests to validate ML integration points: REST/gRPC API calls, feature flags, model versioning, and output accuracy. Include bias, fairness, and edge-case validations in test suites where applicable (e.g., fairness in recommendation engines or NLP sentiment analysis). End-to-End Test Coverage Lead the implementation of end-to-end automation for: Web interfaces (React, Angular, or other SPA frameworks) Backend services (REST, GraphQL, WebSockets) ML model integration endpoints (real-time inference APIs, batch pipelines) Build test utilities for mocking, stubbing, and simulating AI inputs and datasets. CI/CD & Tooling Integration Integrate automation suites into CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI, or similar. Configure parallel execution, containerized test environments (e.g., Docker), and test artifact management. Establish real-time dashboards and historical reporting using tools like Allure, ReportPortal, TestRail, or custom Grafana integrations. Quality Engineering & Leadership Define KPIs and QA metrics for AI/ML product quality: functional accuracy, model regression rates, test coverage %, time-to-feedback, etc. Lead and mentor a team of automation and QA engineers across multiple projects. Act as the Quality Champion across the AI platform by influencing engineering, product, and data science teams on quality ownership and testing best practices. Agile & Cross-Functional Collaboration Work in Agile/Scrum teams; participate in backlog grooming, sprint planning, and retrospectives. Collaborate across disciplines: Frontend, Backend, DevOps, MLOps, and Product Management to ensure complete testability. Review feature specs, AI/ML model update notes, and data schemas for impact analysis. Required Skills and Qualifications: Technical Skills: Strong hands-on expertise with Playwright (TypeScript/JavaScript). Experience building custom automation frameworks and utilities from scratch. Proficiency in testing AI/ML-integrated applications: inference endpoints, personalization engines, chatbots, or predictive dashboards. Solid knowledge of HTTP protocols, API testing (Postman, Supertest, RestAssured). Familiarity with MLOps and model lifecycle management (e.g., via MLflow, SageMaker, Vertex AI). Experience in testing data pipelines (ETL, streaming, batch), synthetic data generation, and test data versioning. Domain Knowledge: Exposure to NLP, CV, recommendation engines, time-series forecasting, or tabular ML models. Understanding of key ML metrics (precision, recall, F1-score, AUC), model drift, and concept drift. Knowledge of bias/fairness auditing, especially in UI/UX contexts where AI decisions are shown to users. Leadership & Communication: Proven experience leading QA/Automation teams (4+ engineers). Strong documentation, code review, and stakeholder communication skills. Experience collaborating in Agile/SAFe environments with cross-functional teams. Preferred Qualifications: Experience with AI Explainability frameworks like LIME, SHAP, or What-If Tool. Familiarity with Test Data Management platforms (e.g., Tonic.ai, Delphix) for ML training/inference data. Background in performance and load testing for AI systems using tools like Locust, JMeter, or k6. Experience with GraphQL, Kafka, or event-driven architecture testing. QA Certifications (ISTQB, Certified Selenium Engineer) or cloud certifications (AWS, GCP, Azure). Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related technical discipline. Bonus for certifications or formal training in Machine Learning, Data Science, or MLOps. Why Join Us? At GRhombus, we are redefining quality assurance and software testing with cutting-edge methodologies and a commitment to innovation. As a test automation lead, you will play a pivotal role in shaping the future of automated testing, optimizing frameworks, and driving efficiency across our engineering ecosystem. Be part of a workplace that values experimentation, learning, and professional growth. Contribute to an organisation where your ideas drive innovation and make a tangible impact. Show more Show less

About the Role We are hiring an AI/ML Engineer based in India. You will help design, develop, optimize, and deploy a multimodal AI models for eye disease screening using image and tabular/textual data. You will collaborate closely with AI researchers, engineers, and product teams to build and translate cutting-edge models. This is an opportunity to work at the frontier of clinical AI with purpose-driven colleagues and powerful social impact. Job Type: Full-Time, Remote Start Date: Immediate Compensation: 35-50 lakh INR, commensurate with experience Responsibilities Design and implement multimodal deep learning models combining image encoders and language models. Train, fine-tune, and optimize models using annotated eye images and structured clinical data. Implement instruction-tuned outputs for diagnosis, referral decisions, and patient counseling in English, Hindi, and Tamil. Optimize inference performance using quantization, pruning, and model distillation for deployment on smartphones or edge devices. Work with mobile and backend engineers to integrate models with our telemedicine app and cloud-based infrastructure. Contribute to model evaluation across clinical sites using real-world patient data to measure accuracy, bias, and latency. Support development of responsible AI pipelines: privacy, bias mitigation, versioning, and drift detection. Qualifications Must-Have: Bachelor’s or Master’s degree in Computer Science, AI, Biomedical Engineering, or related field. 4+ years of experience with deep learning framework (Master’s degree can substitute for experience). Hands-on experience training or fine-tuning transformer models (e.g., LLaMA, T5, GPT). Hands-on experience working with vision models (CNNs, ViTs) Fluency with version control (Git), collaborative workflows, and cloud-based development. Passion for using AI in global health or social impact domains. Preferred: Experience with multimodal fusion techniques (cross-attention, late fusion, MLP). Experience implementing or optimizing Retrieval-Augmented Generation (RAG) pipelines for domain-specific applications (e.g., medical QA, knowledge-grounded generation). Experience working with multilingual NLP/NLG (especially Hindi and Tamil). Prior work with model optimization for edge deployment using ONNX, Core ML, TensorFlow Lite, or quantized PyTorch models, or knowledge of hybrid cloud/on-device design. Proven ability to mentor junior engineers and foster a culture of technical growth and collaboration. Strong written and verbal communication skills with cross-functional stakeholders (e.g., product, clinical, design) Why Join Us Work on a mission-driven project with real clinical impact across underserved communities in India. Flexibility to work remotely while contributing to a globally recognized AI/health project. ( Note : Must be available for 2–3 regularly scheduled Zoom meetings per week and one in-person week per year.) Join a startup-minded team with stable long-term partnerships and funding. Apply here: https://www.visilant.org/careers/aiml-engineer-india-job-post Note: Applications through LinkedIn will not be reviewed. About Visilant: Visilant is a digital health social enterprise spun out of Johns Hopkins University. Visilant builds smartphone-based imaging, telemedicine, and artificial intelligence to empower non-eye care specialists to screen patients leading causes of blindness. Visilant has already screened over 30,000 patients in partnership with the largest eye care systems in India Show more Show less

Role Title : Senior Engineer – AI, CV & Edge Product Development Department : Engineering / Product Development Reports To : Technical Lead → Engineering Manager → Technical Program Manager Location : [Technopark- Trivandrum] Employment Type : Full-time The Senior Engineer – AI & Edge Product Development is responsible for the design, development, integration, and optimization of advanced technology components within AI and computer vision-based product lines. This role spans edge and server hardware, embedded and cloud applications, system utilities and infrastructure alignment. The Senior Engineer contributes technically, drives implementation excellence, and provides mentoring support to junior engineers. Key Responsibilities1. System Design & Development Develop core software modules for edge and server environments including system services, APIs, and AI integration layers. Participate in the design of end-to-end architecture involving AI/CV models, sensor integration, and multi-platform deployment. 2. AI & Computer Vision Implementation Collaborate with data science teams to integrate AI/ML models into production pipelines. Optimize runtime performance and memory utilization for inference on edge devices (e.g., GPU, TPU, ARM platforms). 3. Hardware & Embedded Systems Coordination Ensure compatibility and performance alignment between software applications and underlying edge or server hardware. Work on low-level device interfaces, sensor control, and real-time data acquisition when required. 4. Application and Utility Development Contribute to the development of utilities for diagnostics, licensing, system configuration, remote updates, and monitoring. Ensure robust, user-oriented, and secure implementation of all services. 5. Infrastructure & Deployment Support Support infrastructure sizing and configuration based on AI workload profiles, latency requirements, and deployment architecture. Collaborate with DevOps for containerization, CI/CD setup, and deployment automation across environments. 7. Code Quality & Documentation Write clean, maintainable, and scalable code with unit tests and inline documentation. Participate in code reviews, performance tuning, and system debugging efforts. 8. Mentorship & Team Collaboration Provide technical mentorship to junior engineers and interns. Collaborate with product, QA, infrastructure, and hardware teams for coordinated execution. Required Qualifications & Skills Bachelor’s or Master’s degree in Computer Science, Electronics, Electrical Engineering, or a related field. 4+ years of hands-on engineering experience in product development, preferably in AI/CV-enabled or embedded systems. Strong programming skills in Python, C++, or C with experience in multi-threaded and real-time systems. Practical experience with AI inference engines and edge deployment tools. Experience working on edge platforms and server-based deployment environments. Familiarity with REST APIs, licensing SDKs, Docker/Kubernetes, Linux environments. Preferred Attributes Self-motivated and technically curious with a hands-on problem-solving approach. Good understanding of hardware-software co-design, deployment constraints, and cross-platform development. Strong interpersonal skills with the ability to work collaboratively across disciplines. Exposure to regulated environments or mission-critical deployments is a plus. Show more Show less

AI Fullstack Engineer Experience: 4 - 9 Years Exp Salary : Competitive Preferred Notice Period : Within 30 Days Opportunity Type: Remote Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills required : Python, Angular, AWS HurixDigital (One of Uplers' Clients) is Looking for: AI Fullstack Engineer who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you. Job Description Key Responsibilities Develop and deploy end-to-end AI-powered applications leveraging full-stack development best practices. Architect and integrate AI/ML models and pipelines using tools like LangChain, Hugging Face, OpenAI, and Anthropic Claude APIs. Design and implement microservices, RESTful APIs, and backend systems with scalability and maintainability in mind. Leverage cloud platforms (AWS, Azure, GCP) for hosting, automation, and scaling services. Integrate CI/CD pipelines to ensure smooth and frequent deployment cycles. Collaborate with cross-functional teams to translate business requirements into technical solutions. Apply techniques such as content chunking, vector search, embedding models, and retrievers to build advanced AI retrieval systems. Ensure robust architecture that can withstand variable load conditions, focusing on fault tolerance and high availability. Maintain documentation and adhere to best practices in software development and AI model integration. Required Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 5+ years of hands-on experience in AI engineering and full-stack development. Strong proficiency with AI/ML tools including LangChain, Hugging Face, OpenAI, and Claude APIs. Deep understanding of vector databases, retrievers, and modern NLP workflows. Proficient in one or more full-stack frameworks (e.g., Node.js, Django, React, Angular). Experience with cloud platforms (AWS, Azure, GCP) and infrastructure automation tools (e.g., Terraform, CloudFormation). Solid experience with CI/CD pipelines, GitOps, and container orchestration (e.g., Docker, Kubernetes). Proven ability to architect resilient systems and optimize performance under fluctuating workloads. Preferred Skills Knowledge of prompt engineering and LLM fine-tuning techniques. Familiarity with DevSecOps practices and AI compliance requirements. Exposure to multimodal models and real-time inference systems. How to apply for this opportunity: Easy 3-Step Process: 1. Click On Apply! And Register or log in on our portal 2. Upload updated Resume & Complete the Screening Form 3. Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring and getting hired reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career. (Note: There are many more opportunities apart from this on the portal.) So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less