1535 Mlflow Jobs - Page 42

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. Primary Responsibilities: WHAT Business Knowledge: Capable of understanding the requirements for the entire project (not just own features) Capable of working closely with PMG during the design phase to drill down into detailed nuances of the requirements Has the ability and confidence to question the motivation behind certain requirements and work with PMG to refine them. Design: Can design and implement machine learning models and algorithms Can articulate and evaluate pros/cons of different AI/ML approaches Can generate cost estimates for model training and deployment Coding/Testing: Builds and optimizes machine learning pipelines Knows & brings in external ML frameworks and libraries Consistently avoids common pitfalls in model development and deployment HOW Quality: Solves cross-functional problems using data-driven approaches Identifies impacts/side effects of models outside of immediate scope of work Identifies cross-module issues related to data integration and model performance Identifies problems predictively using data analysis Productivity: Capable of working on multiple AI/ML projects simultaneously and context switching between them Process: Enforces process standards for model development and deployment. Independence: Acts independently to determine methods and procedures on new or special assignments Prioritizes large tasks and projects effectively Agility: Release Planning: Works with the PO to do high-level release commitment and estimation Works with PO on defining stories of appropriate size for model development Agile Maturity: Able to drive the team to achieve a high level of accomplishment on the committed stories for each iteration Shows Agile leadership qualities and leads by example WITH Team Work: Capable of working with development teams and identifying the right division of technical responsibility based on skill sets. Capable of working with external teams (e.g., Support, PO, etc.) that have significantly different technical skill sets and managing the discussions based on their needs Initiative: Capable of creating innovative AI/ML solutions that may include changes to requirements to create a better solution Capable of thinking outside-the-box to view the system as it should be rather than only how it is Proactively generates a continual stream of ideas and pushes to review and advance ideas if they make sense Takes initiative to learn how AI/ML technology is evolving outside the organization Takes initiative to learn how the system can be improved for the customers Should make problems open new doors for innovations Communication: Communicates complex AI/ML concepts internally with ease Accountability: Well versed in all areas of the AI/ML stack (data preprocessing, model training, evaluation, deployment, etc.) and aware of all components in play Leadership: Disagree without being disagreeable Use conflict as a way to drill deeper and arrive at better decisions Frequent mentorship Builds ad-hoc cross-department teams for specific projects or problems Can achieve broad scope 'buy in' across project teams and across departments Takes calculated risks Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: B.E/B.Tech/MCA/MSc/MTech (Minimum 16 years of formal education, Correspondence courses are not relevant) 5+ years of experience working on multiple layers of technology Experience deploying and maintaining ML models in production Experience in Agile teams Experience with one or more data-oriented workflow orchestration frameworks (Airflow, KubeFlow etc.) Working experience or good knowledge of cloud platforms (e.g., Azure, AWS, OCI) Ability to design, implement, and maintain CI/CD pipelines for MLOps and DevOps function Familiarity with traditional software monitoring, scaling, and quality management (QMS) Knowledge of model versioning and deployment using tools like MLflow, DVC, or similar platforms Familiarity with data versioning tools (Delta Lake, DVC, LakeFS, etc.) Demonstrate hands-on knowledge of OpenSource adoption and use cases Good understanding of Data/Information security Proficient in Data Structures, ML Algorithms, and ML lifecycle Product/Project/Program Related Tech Stack: Machine Learning Frameworks: Scikit-learn, TensorFlow, PyTorch Programming Languages: Python, R, Java Data Processing: Pandas, NumPy, Spark Visualization: Matplotlib, Seaborn, Plotly Familiarity with model versioning tools (MLFlow, etc.) Cloud Services: Azure ML, AWS SageMaker, Google Cloud AI GenAI: OpenAI, Langchain, RAG etc. Demonstrate good knowledge in Engineering Practices Demonstrates excellent problem-solving skills Proven excellent verbal, written, and interpersonal communication skills At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

Job Description: Who are we Infosys NYSE INFY is a global leader in consulting technology and outsourcing solutions with annual revenues of over 15 64 B as of 2022 We enable clients in more than 50 countries to stay a step ahead of emerging business trends and outperform the competition Infosys Recognized as one of the 2022 World s Most Ethical Companies for the Second Consecutive Year by Ethisphere What are we looking for Lead Machine Learning Engineer We are looking for smart self driven high energy people with top notch communication skills intellectual curiosity and passion for technology in Machine Learning Space Our analysts have a blend of in depth domain expertise in one or more areas Retail CPG Logistics strong business and technical acumen along with excellent soft skills What do we require To work with clients to understand the issues they face diagnose problems design solutions and facilitate solution deployment on Azure ML One can be an individual contributor or lead small teams depending on the project You will be pivotal to understanding the requirement problem definition and discovery of the overall solution One will also have the opportunity to shape value adding consulting solutions for clients by connecting various functions of cloud components Industry knowledge Knows basics of machine learning is aware of cloud services Azure services has a deep understanding of coding practices knows how to guide teams on debugging the issues can connect the dots to arrivie at a solution and is very good at presentation of the ideas thoughts and solutions Key Responsibilities: Technical knowledge has expertise in cloud technologies specifically MS Azure and services with hands on coding to Expertise in Object Oriented Python Programming with 6 8 years experience DevOps Working knowledge with implementation experience 1 or 2 projects a minimum Hands On MS Azure Cloud knowledge Understand and take requirements on Operationalization of ML Models from Data Scientist Help team with ML Pipelines from creation to execution List Azure services required for deployment Azure Data bricks and Azure DevOps Setup Assist team to coding standards flake8 etc Guide team to debug on issues with pipeline failures Engage with Business Stakeholders with status update on progress of development and issue fix Automation Technology and Process Improvement for the deployed projects Setup Standards related to Coding Pipelines and Documentation Adhere to KPI SLA for Pipeline Run Execution Research on new topics services and enhancements in Cloud Technologies Domain Technical Tools Knowledge Object oriented programming coding standards architecture design patterns Config management Package Management Logging documentation Experience in Test Driven Development and experience in using Pytest frameworks git version control Rest APIs Python programming with OOPs concept SQL XML YAML Bash JSON Pydantic models Class based frameworks Dependency injections FastAPI Flask Streamlit Python Azure API management API Gateways Traffic Manager Load Balancers Nginx Uvicorn Gunicorn Azure ML best practices in environment management run time configurations Azure ML Databricks clusters alerts Experience designing and implementing ML Systems pipelines MLOps practices and tools such a MLFlow Kubernetes etc Exposure to event driven orchestration Online Model deployment Contribute towards establishing best practices in MLOps Systems development Proficiency with data analysis tools e g SQL R Python High level understanding of database concepts reporting Data Science concepts Hands on experience in working with client IT Business teams in gathering business requirement and converting into requirement for development team Experience in managing client relationship and developing business cases for opportunities Azure AZ 900 Certification with Azure Architect Technical Requirements: Primary skills Technology OpenSystem Python OpenSystem Responsible for successful delivery of MLOps solutions and services in client consulting environments Define key business problems to be solved formulate high level solution approaches and identify data to solve those problems develop analyze draw conclusions and present to client Assist clients with operationalization metrics to track performance of ML Models Agile trained to manage team effort and track through JIRA High Impact Communication Assesses the target audience need prepares and practices a logical flow answers audience questions appropriately and sticks to timeline Additional Responsibilities: Good knowledge on software configuration management systems Strong business acumen strategy and cross industry thought leadership Awareness of latest technologies and Industry trends Education and Experience Overall 6 to 8 years of experience in Data driven software engineering with 3 5 years of experience designing building and deploying enterprise AI or ML applications with at least 2 years of experience implementing full lifecycle ML automation using MLOps scalable development to deployment of complex data science workflows Bachelors or Master s degree in Computer Science Engineering or equivalent Domain experience in Retail CPG and Logistics etc Azure Certified DP100 AZ AI900 Logical thinking and problem solving skills along with an ability to collaborate Two or three industry domain knowledge Understanding of the financial processes for various types of projects and the various pricing models available Client Interfacing skills Knowledge of SDLC and agile methodologies Project and Team management Preferred Skills: Technology->OpenSystem->Python - OpenSystem->Python

Job Description: Who are we Infosys NYSE INFY is a global leader in consulting technology and outsourcing solutions with annual revenues of over 15 64 B as of 2022 We enable clients in more than 50 countries to stay a step ahead of emerging business trends and outperform the competition Infosys Recognized as one of the 2022 World s Most Ethical Companies for the Second Consecutive Year by Ethisphere What are we looking for Lead Machine Learning Engineer We are looking for smart self driven high energy people with top notch communication skills intellectual curiosity and passion for technology in Machine Learning Space Our analysts have a blend of in depth domain expertise in one or more areas Retail CPG Logistics strong business and technical acumen along with excellent soft skills What do we require To work with clients to understand the issues they face diagnose problems design solutions and facilitate solution deployment on Azure ML One can be an individual contributor or lead small teams depending on the project You will be pivotal to understanding the requirement problem definition and discovery of the overall solution One will also have the opportunity to shape value adding consulting solutions for clients by connecting various functions of cloud components Industry knowledge Knows basics of machine learning is aware of cloud services Azure services has a deep understanding of coding practices knows how to guide teams on debugging the issues can connect the dots to arrivie at a solution and is very good at presentation of the ideas thoughts and solutions Key Responsibilities: Technical knowledge has expertise in cloud technologies specifically MS Azure and services with hands on coding to Expertise in Object Oriented Python Programming with 4 5 years experience DevOps Working knowledge with implementation experience 1 or 2 projects a minimum Hands On MS Azure Cloud knowledge Understand and take requirements on Operationalization of ML Models from Data Scientist Help team with ML Pipelines from creation to execution List Azure services required for deployment Azure Data bricks and Azure DevOps Setup Assist team to coding standards flake8 etc Guide team to debug on issues with pipeline failures Engage with Business Stakeholders with status update on progress of development and issue fix Automation Technology and Process Improvement for the deployed projects Setup Standards related to Coding Pipelines and Documentation Adhere to KPI SLA for Pipeline Run Execution Research on new topics services and enhancements in Cloud Technologies Technical Requirements: Education and Experience Overall 6 to 8 years of experience in Data driven software engineering with 3 5 years of experience designing building and deploying enterprise AI or ML applications with at least 2 years of experience implementing full lifecycle ML automation using MLOps scalable development to deployment of complex data science workflows Bachelors or Master s degree in Computer Science Engineering or equivalent Domain experience in Retail CPG and Logistics etc Azure Certified DP100 AZ AI900 Additional Responsibilities: Domain Technical Tools Knowledge Object oriented programming coding standards architecture design patterns Config management Package Management Logging documentation Experience in Test Driven Development and experience in using Pytest frameworks git version control Rest APIs Azure ML best practices in environment management run time configurations Azure ML Databricks clusters alerts Experience designing and implementing ML Systems pipelines MLOps practices and tools such a MLFlow Kubernetes etc Exposure to event driven orchestration Online Model deployment Contribute towards establishing best practices in MLOps Systems development Proficiency with data analysis tools e g SQL R Python High level understanding of database concepts reporting Data Science concepts Hands on experience in working with client IT Business teams in gathering business requirement and converting into requirement for development team Experience in managing client relationship and developing business cases for opportunities Azure AZ 900 Certification with Azure Architecture understanding is a plus Preferred Skills: Technology->Data Science->Machine Learning

We’re looking for an experienced AI Developer to join our team and drive the design, development, and deployment of advanced computer-vision and LLM-based solutions. You’ll build real-time object detection & tracking pipelines (LLM, YOLOv8/11), develop face-recognition models on video feeds with LLM support, and manage GPU-powered server infrastructure end-to-end. Key Responsibilities Model Development & Optimization Design, train, and fine-tune LLMs, YOLOv8/11 models for multi-class object detection. Implement face-recognition pipelines leveraging state-of-the-art LLMs and embedding techniques. Optimize inference speed and accuracy for real-time video processing on GPUs. Video Analytics & Tracking Develop multi-camera object-tracking algorithms across disparate video sources. Integrate OpenCV, DeepSORT (or similar), and custom tracking logic for robust performance. Infrastructure & Deployment Provision and maintain Linux servers with SSH, Docker, and GPU drivers (NVIDIA CUDA/cuDNN). Automate CI/CD pipelines for model training, evaluation, and deployment. Monitor GPU utilization, troubleshoot performance bottlenecks, and ensure high availability. Collaboration & Documentation Work closely with product managers, data engineers, and front-end teams to integrate AI services via REST/gRPC APIs. Write clear technical documentation, API specs, and best-practice guides. Required Qualifications Bachelor’s or Master’s in Computer Science, Electrical Engineering, or related field. 2-3+ years hands-on experience with: YOLOv8 or YOLOv11 (training, inference, transfer learning) Face recognition frameworks (InsightFace, FaceNet, ArcFace) and LLM embeddings (e.g., Hugging Face Transformers) Python ecosystem: PyTorch/TensorFlow, OpenCV, NumPy, scikit-learn Strong Linux skills: server provisioning, SSH, shell scripting. Proficiency in managing GPU servers (NVIDIA CUDA, Docker GPU containers) Experience deploying models in production (AWS/GCP/Azure or on-prem clusters). Preferred Qualifications Familiarity with video-streaming protocols (RTSP/WebRTC). Knowledge of microservices architecture and API gateways. Exposure to MLOps platforms (MLflow, Kubeflow). Strong debugging, profiling, and performance-tuning abilities. Job Types: Full-time, Permanent Pay: ₹800,000.00 - ₹1,200,000.00 per year Benefits: Flexible schedule Paid sick time Paid time off Provident Fund Location Type: In-person Schedule: Fixed shift Ability to commute/relocate: Mumbai, Maharashtra: Reliably commute or planning to relocate before starting work (Preferred) Experience: AI: 2 years (Preferred) Work Location: In person Speak with the employer +91 9830000000

Job Description Publicis Sapient is looking for an experienced Manager, Machine Learning Engineering to lead our talented team of AI and data science experts. In this influential role, you will be responsible for developing and implementing solutions that address complex business challenges across a wide range of industries. Your expertise will empower clients to revolutionize their businesses by harnessing the potential of advanced technology. As a Manager, Machine Learning Engineering, you will collaborate with cross-functional teams to strategize, develop, and deliver machine learning models tailored to meet specific business objectives. You will be responsible for overseeing the entire lifecycle of these models, from data preprocessing and algorithm selection to performance evaluation and seamless integration into production systems. Your Impact As a Manager Data Science specialising in Generative AI, you will: Lead AI-Driven Innovations: Drive the development of state-of-the-art AI and machine learning solutions that transform business strategies and deliver exceptional customer experiences. Strategic Collaboration: Work closely with cross-functional teams, including product managers, data engineers, and business stakeholders, to define and execute data-driven solutions aligned with organizational goals. Foster a High-Performance Team: Build, mentor, and lead a team of talented data scientists, cultivating a culture of innovation, collaboration, and continuous learning. Deliver Business Impact: Translate complex business problems into AI/ML solutions by leveraging advanced techniques such as generative AI, deep learning, and NLP, ensuring measurable outcomes. Optimize AI Pipelines: Oversee the development and deployment of scalable, efficient, and robust machine learning pipelines that address latency, responsiveness, and real-time data processing challenges. Customize AI Models: Direct the customization and fine-tuning of AI models, including large language models (LLMs) and other generative AI technologies, to meet domain-specific requirements. Promote Data-Driven Decision-Making: Advocate for data-centric approaches across teams, ensuring data quality, integrity, and readiness to maximize model performance and business impact. Develop Intelligent AI Agents: Architect and refine AI agents that solve complex business challenges, leveraging LLMs to deliver personalized, user-centric solutions. Advance Generative AI Applications: Innovate with cutting-edge generative AI models such as LLM, VLM, GANs, and VAEs to create tailored applications for dynamic content creation, predictive analytics, and enhanced automation. Scale AI with Cloud Technology: Deploy and scale LLM-based solutions on platforms like GCP, AWS and Azure to address real-world business problems with precision and efficiency. Stay at the Cutting Edge: Keep up-to-date with emerging trends and innovations in AI and data science, identifying opportunities to incorporate the latest advancements into projects. Qualifications 8 years to 15 years with at least 2 years of Gen AI experience 8 years to 15 years with at least 2 years of Gen AI experience Qualification: 8-14 Years with 2 Yrs Gen AI Your Skills & Experience Fine tuning experience of Large Language models (LLMs, VLLMs, or Vision model) Distributed training or inference experience with frameworks like Ray, vllm, openllm, bentoML etc. Experience with frameworks like like LangChain, Llamaindex for building maintainable, scalable Generative AI applications. Deployment experience or optimized hosting experience of Large Language models (LLMs, VLLMs, or Vision model) Experience working with any Vector database like Milvus, FAISS, ChromaDB etc Experience developing agents with frameworks like LangGraph, CrewAI, Autogen etc Experience with prompt engineering Keeping up with latest market trends Experience working with open source large language models from HuggingFace Experience working with atleast one public cloud provider such as Azure, AWS or GCP Experience working with container technology like Docker, ECS etc Experience with DevOps practices and CI/CD pipelines for data solutions Experience in deploying solutions to production with Kubernetes or OpenShift Experience with managing ML workflows with MLFlow or KubeFlow. Additional Information A Tip From The Hiring Manager Join the team to sharpen your skills and expand your collaborative methods. Make an impact on our clients and their businesses directly through your work. Additional Information Gender Neutral Policy 18 paid holidays throughout the year Generous parental leave and new parent transition program Flexible work arrangements Employee Assistance Programs to help you in wellness and well being Company Description Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally-enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting, and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of the next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting and customer obsession to accelerate our clients’ businesses through designing the products and services their customers truly value. Show more Show less

About Us: Athena is India's largest institution in the "premium undergraduate study abroad" space. Founded 10 years ago by two Princeton graduates, Poshak Agrawal and Rahul Subramaniam, Athena is headquartered in Gurgaon, with offices in Mumbai and Bangalore, and caters to students from 26 countries. Athena’s vision is to help students become the best version of themselves. Athena’s transformative, holistic life coaching program embraces both depth and breadth, sciences and the humanities. Athena encourages students to deepen their theoretical knowledge and apply it to address practical issues confronting society, both locally and globally. Through our flagship program, our students have gotten into various, universities including Harvard University, Princeton University, Yale University, Stanford University, University of Cambridge, MIT, Brown, Cornell University, University of Pennsylvania, University of Chicago, among others. Learn more about Athena: https://www.athenaeducation.co.in/article.aspx Role Overview We are looking for an AI/ML Engineer who can mentor high-potential scholars in creating impactful technology projects. This role requires a blend of strong engineering expertise, the ability to distill complex topics into digestible concepts, and a deep passion for student-driven innovation. You’ll help scholars explore the frontiers of AI—from machine learning models to generative AI systems—while coaching them in best practices and applied engineering. Key Responsibilities: Guide scholars through the full AI/ML development cycle—from problem definition, data exploration, and model selection to evaluation and deployment. Teach and assist in building: Supervised and unsupervised machine learning models. Deep learning networks (CNNs, RNNs, Transformers). NLP tasks such as classification, summarization, and Q&A systems. Provide mentorship in Prompt Engineering: Craft optimized prompts for generative models like GPT-4 and Claude. Teach the principles of few-shot, zero-shot, and chain-of-thought prompting. Experiment with fine-tuning and embeddings in LLM applications. Support scholars with real-world datasets (e.g., Kaggle, open data repositories) and help integrate APIs, automation tools, or ML Ops workflows. Conduct internal training and code reviews, ensuring technical rigor in projects. Stay updated with the latest research, frameworks, and tools in the AI ecosystem. Technical Requirements: Proficiency in Python and ML libraries: scikit-learn, XGBoost, Pandas, NumPy. Experience with deep learning frameworks : TensorFlow, PyTorch, Keras. Strong command of machine learning theory , including: Bias-variance tradeoff, regularization, and model tuning. Cross-validation, hyperparameter optimization, and ensemble techniques. Solid understanding of data processing pipelines , data wrangling, and visualization (Matplotlib, Seaborn, Plotly). Advanced AI & NLP Experience with transformer architectures (e.g., BERT, GPT, T5, LLaMA). Hands-on with LLM APIs : OpenAI (ChatGPT), Anthropic, Cohere, Hugging Face. Understanding of embedding-based retrieval , vector databases (e.g., Pinecone, FAISS), and Retrieval-Augmented Generation (RAG). Familiarity with AutoML tools , MLflow, Weights & Biases, and cloud AI platforms (AWS SageMaker, Google Vertex AI). Prompt Engineering & GenAI Proficiency in crafting effective prompts using: Instruction tuning Role-playing and system prompts Prompt chaining tools like LangChain or LlamaIndex Understanding of AI safety , bias mitigation, and interpretability. Required Qualifications: Bachelor’s degree from a Tier-1 Engineering College in Computer Science, Engineering, or a related field. 2-5 years of relevant experience in ML/AI roles. Portfolio of projects or publications in AI/ML (GitHub, blogs, competitions, etc.) Passion for education, mentoring , and working with high school scholars. Excellent communication skills, with the ability to convey complex concepts to a diverse audience. Preferred Qualifications: Prior experience in student mentorship, teaching, or edtech. Exposure to Arduino, Raspberry Pi, or IoT for integrated AI/ML projects. Strong storytelling and documentation abilities to help scholars write compelling project reports and research summaries. Show more Show less

🔧 Job Opening: MLOps & DevOps Engineer 📍 Location : Pune, India | 🧠 Experience : 3–5 Years 🕒 Immediate Joiners Preferred Company : Asmadiya Technologies Pvt. Ltd. About Us: Asmadiya Technologies is a dynamic technology company delivering innovative solutions in AI/ML , Cloud Computing , and Digital Transformation . We are seeking an experienced MLOps & DevOps Engineer to join our engineering team and lead the development, deployment, and monitoring of machine learning systems in production. ✅ Key Responsibilities: Design and implement CI/CD pipelines for ML models and microservices Manage end-to-end MLOps workflows – from model training, versioning, deployment, to monitoring Automate infrastructure using Terraform, CloudFormation , or similar tools Integrate ML workflows with cloud platforms like AWS, Azure, or GCP Implement model registry , artifact tracking, and monitoring (e.g., MLflow, Weights & Biases) Collaborate with Data Scientists, ML Engineers, and DevOps teams to ensure scalable and reliable deployments Set up and maintain Kubernetes (EKS/AKS/GKE) clusters and orchestrate model serving Ensure compliance, security, and reliability of deployed systems Proactively identify performance bottlenecks and implement optimization 🧩 Required Skills & Experience: 3–5 years of experience in DevOps and MLOps environments Strong expertise in Docker, Kubernetes, Jenkins/GitHub Actions/GitLab CI Hands-on experience with ML lifecycle tools : MLflow, Kubeflow, SageMaker, or similar Proficient in scripting with Python , Bash , and using Linux-based systems Experience with infrastructure-as-code (Terraform, Ansible, Helm) Working knowledge of cloud platforms (AWS preferred) and model deployment at scale Familiar with observability tools like Prometheus, Grafana, or ELK stack 🌟 What We’re Looking For: A problem-solver who can bridge the gap between data science and operations A hands-on contributor who can own deployments end-to-end A collaborative team player who thrives in fast-paced, agile environments Passionate about building production-ready ML systems 📬 Apply Now: Looking to lead the charge in deploying intelligent systems at scale? Join Asmadiya Technologies as we build the future of AI. 📩 Send your resume to careers@asmadiya.com with subject: MLOps & DevOps Engineer – Pune Show more Show less

Associate Director - AI/ML Engineering What you will do Let’s do this. Let’s change the world. We are seeking a Associate Director of ML / AI Engineering to lead Amgen India’s AI engineering practice. This role is integral to developing top-tier talent, setting ML / AI best practices, and evangelizing ML / AI Engineering capabilities across the organization. The Associate Director will be responsible for driving the successful delivery of strategic business initiatives by overseeing the technical architecture, managing talent, and establishing a culture of excellence in ML / AI The key aspects of this role involve : (1) prior hands-on experience building ML and AI solutions (2) management experience in leading ML / AI engineering team and talent development (3) Delivering AI initiatives at enterprise scale Roles & Responsibilities: Talent Growth & People Leadership: Lead, mentor, and manage a high-performing team of engineers, fostering an environment that encourages learning, collaboration, and innovation. Focus on nurturing future leaders and providing growth opportunities through coaching, training, and mentorship. Recruitment & Team Expansion: Develop a comprehensive talent strategy that includes recruitment, retention, onboarding, and career development and build a diverse and inclusive team that drives innovation, aligns with Amgen's culture and values, and delivers business priorities Organizational Leadership: Work closely with senior leaders within the function and across the Amgen India site to align engineering goals with broader organizational objectives and demonstrate leadership by contributing to strategic discussions Create and implement a strategy for expanding the AI/ML engineering team, including recruitment, onboarding, and talent development. Oversee the end-to-end lifecycle of AI/ML projects, from concept and design through to deployment and optimization, ensuring timely and successful delivery. Ensure adoption of ML-Ops best practices, including model versioning, testing, deployment, and monitoring. Collaborate with multi-functional teams, including product, data science, and software engineering, to find opportunities and deliver AI/ML solutions that drive business value. Serve as an AI/ML evangelist across the organization, promoting awareness and understanding of the capabilities and value of AI/ML technologies. Promote a culture of innovation and continuous learning within the team, encouraging the exploration of new tools, technologies, and methodologies. Provide technical leadership and mentorship, guiding engineers in implementing scalable and robust AI/ML systems. Work closely with collaborators to prioritize AI/ML projects and ensure timely delivery of key initiatives. Lead innovation initiatives to explore new AI/ML technologies, platforms, and tools that can drive further advancements in the organization’s AI capabilities. What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: Master’s degree and 12 to 14 years of computer science, Artificial Intelligence, Machine Learning experience OR Bachelor’s degree and 14 to 18 years of computer science, Artificial Intelligence, Machine Learning experience OR Diploma and 18 to 20 years of computer science, Artificial Intelligence, Machine Learning experience Preferred Qualifications: Experience in building AI Platforms & applications at enterprise scale Expertise in AI/ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc. Hands-on experience with LLMs, Generative AI, and NLP (e.g., GPT, BERT, Llama, Claude, Mistral AI ) Strong understanding of MLOps processes and tools such as MLflow, Kubeflow, or similar platforms. Proficient in programming languages such as Python, R, or Scala. Experience deploying AI/ML models in cloud environments (AWS, Azure, or Google Cloud). Proven track record of managing and delivering AI/ML projects at scale. Excellent project management skills, with the ability to lead multi-functional teams and manage multiple priorities. Experience in regulated industries, preferably life sciences and pharma Good-to-Have Skills: Experience with natural language processing, computer vision, or reinforcement learning. Knowledge of data governance, privacy regulations, and ethical AI considerations. Experience with cloud-native AI/ML services (Databricks, AWS, Azure ML, Google AI Platforms) Experience with AI Observability Professional Certifications (Preferred): Google Professional Machine Learning Engineer, AWS Certified Machine Learning, or Azure AI Engineer Associate, Databricks Certified Generative AI Engineer Associate Soft Skills: Excellent leadership and communication skills, with the ability to convey complex technical concepts to non-technical collaborators. Ability to foster a collaborative and innovative work environment. Strong problem-solving abilities and attention to detail. High degree of initiative and self-motivation. Ability to mentor and develop team members, promoting their growth and success. Show more Show less

Role: Senior Analyst Experience: 3 to 5 years Location: Bangalore Job Description: Focus on ML model load testing and creation of E2E test cases Evaluate models’ scalability and latency by running suites of metrics under different RPS and creating and automating the test cases for individual models, ensuring a smooth rollout of the models Enhance monitoring of model scalability, and handle incident of increased error rate Collaborate with existing machine learning engineers, backend engineers and QA test engineers from cross-functional teams Job Responsibilities: Focus on ML model load testing and creation of E2E test cases Evaluate models’ scalability and latency by running suites of metrics under different RPS and creating and automating the test cases for individual models, ensuring a smooth rollout of the models Enhance monitoring of model scalability, and handle incident of increased error rate Collaborate with existing machine learning engineers, backend engineers and QA test engineers from cross-functional teams Skills Required Databricks ; mlFlow ; Seldon ; Kubeflow ; Tecton ; Jenkins ; AWS services , At least one of the programing languages among (Java, Python, Scala) ; ML Load Testing , Job Monitoring , Evaluate Scalability & latency of models , Good communication skills ; Experience with production level Models , worked on models with high data volumes with low latency Job Snapshot Updated Date 10-06-2025 Job ID J_3721 Location Bengaluru, Karnataka, India Experience 3 - 5 Years Employee Type Permanent

Category: Software Development/ Engineering Main location: India, Karnataka, Bangalore Position ID: J0625-0079 Employment Type: Full Time Position Description: Company Profile: Founded in 1976, CGI is among the largest independent IT and business consulting services firms in the world. With 94,000 consultants and professionals across the globe, CGI delivers an end-to-end portfolio of capabilities, from strategic IT and business consulting to systems integration, managed IT and business process services and intellectual property solutions. CGI works with clients through a local relationship model complemented by a global delivery network that helps clients digitally transform their organizations and accelerate results. CGI Fiscal 2024 reported revenue is CA$14.68 billion and CGI shares are listed on the TSX (GIB.A) and the NYSE (GIB). Learn more at cgi.com. Position: Manage Consulting Expert- AI Architect Experience: 13-16 years Category: Software Development/ Engineering Shift Timing: General Shift Location: Bangalore Position ID: J0625-0079 Employment Type: Full Time Education Qualification: Bachelor's degree in Computer Science or related field or higher with minimum 13 years of relevant experience. We are looking for an experienced and visionary AI Architect with a strong engineering background and hands-on implementation experience to lead the development and deployment of AI-powered solutions. The ideal candidate will have a minimum of 13–16 years of experience in software and AI systems design, including extensive exposure to large language models (LLMs), vector databases, and modern AI frameworks such as LangChain. This role requires a balance of strategic architectural planning and tactical engineering execution, working across teams to bring intelligent applications to life. Your future duties and responsibilities: Design robust, scalable architectures for AI/ML systems, including LLM-based and generative AI solutions. Lead the implementation of AI features and services in enterprise-grade products with clear, maintainable code. Develop solutions using LangChain, orchestration frameworks, and vector database technologies. Collaborate with product managers, data scientists, ML engineers, and business stakeholders to gather requirements and translate them into technical designs. Guide teams on best practices for AI system integration, deployment, and monitoring. Define and implement architecture governance, patterns, and reusable frameworks for AI applications. Stay current with emerging AI trends, tools, and methodologies to continuously enhance architecture strategy. Oversee development of Proof-of-Concepts (PoCs) and Minimum Viable Products (MVPs) to validate innovative ideas. Ensure systems are secure, scalable, and high-performing in production environments. Mentor junior engineers and architects to build strong AI and engineering capabilities within the team. Required qualifications to be successful in this role: Must to have Skills- 13–16 years of overall experience in software development, with at least 5+ years in AI/ML system architecture and delivery. Proven expertise in developing and deploying AI/ML models in production environments. Deep knowledge of LLMs, LangChain, prompt engineering, RAG (retrieval-augmented generation), and vector search. Strong programming and system design skills with a solid engineering foundation. Exceptional ability to communicate complex concepts clearly to technical and non-technical stakeholders. Experience with Agile methodologies and cross-functional team leadership. Programming Languages: Python, Java, Scala, SQL AI/ML Frameworks: LangChain, TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers Data Processing: Apache Spark, Kafka, Pandas, Dask Vector Stores & Retrieval Systems: FAISS, Pinecone, Weaviate, Chroma Cloud Platforms: AWS (SageMaker, Lambda), Azure (ML Studio, OpenAI), Google Cloud AI MLOps & DevOps: Docker, Kubernetes, MLflow, Kubeflow, Airflow, CI/CD tools (GitHub Actions, Jenkins) Databases: PostgreSQL, MongoDB, Redis, BigQuery, Snowflake Tools & Platforms: Databricks, Jupyter Notebooks, Git, Terraform Good to have Skills- Solution Engineering and Implementation Experience in AI Project. Skills: AWS Machine Learning English GitHub Python Jenkins Kubernetes Prometheus Snowflake What you can expect from us: Together, as owners, let’s turn meaningful insights into action. Life at CGI is rooted in ownership, teamwork, respect and belonging. Here, you’ll reach your full potential because… You are invited to be an owner from day 1 as we work together to bring our Dream to life. That’s why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our company’s strategy and direction. Your work creates value. You’ll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas, embrace new opportunities, and benefit from expansive industry and technology expertise. You’ll shape your career by joining a company built to grow and last. You’ll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons. Come join our team—one of the largest IT and business consulting services firms in the world.

Senior AI Engineer Location: Infopark, Thrissur, Kerala Employment Type: Full-Time Experience Required: Minimum 5 Years providing AI Solutions, including expertise in ML/DL Projects About Us JK Lucent is a growing IT services provider headquartered in Melbourne, Australia, with an operations centre at Infopark, Thrissur, Kerala. We specialize in Software Development, Software Testing, Game Development, RPA, Data Analytics, and AI solutions. At JK Lucent, we are driven by innovation and committed to delivering cutting-edge technology services that solve real-world problems and drive digital transformation. About the Role We are looking for a highly skilled and experienced Senior AI Engineer to lead the development and deployment of advanced AI systems. This role requires deep expertise in Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs). The successful candidate will work on complex AI initiatives, contribute to production-ready systems, and mentor junior engineers. A strong command of professional English and the ability to communicate technical concepts clearly is essential. Roles and Responsibilities Design and develop scalable AI and ML models for real-world applications. Build, fine-tune, and implement Large Language Models (LLMs) for use cases such as chatbots, summarization, and document intelligence. Work with deep learning frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers. Collaborate with cross-functional teams to translate business problems into AI solutions with necessary visualizations using tools like Tableau or Power BI. Deploy models to production environments and implement monitoring and model retraining pipelines. Stay up to date with the latest research and trends in AI, especially in LLMs and generative models. Guide and mentor junior AI engineers, reviewing code and providing technical leadership. Contribute to technical documentation, architecture design, and solution strategies. Ensure models are developed and used ethically and comply with data privacy standards. Requirements Minimum 5 years of experience in AI/ML development with hands-on expertise in model design, development, and deployment. Strong experience working with LLMs and Generative AI tools such as Hugging Face Hub, LangChain, Haystack, LLaMA, GPT, BERT, and T5. Proficiency in Python and ML/DL libraries such as TensorFlow, PyTorch, XGBoost, scikit-learn, and Hugging Face Transformers. Solid understanding of mathematics, statistics, and applied data science principles. Experience deploying models using Docker, FastAPI, MLflow, or similar tools. Familiarity with cloud platforms (AWS, Azure, or GCP) and their AI/ML services. Demonstrated experience in working on end-to-end AI solutions in production environments. Excellent English communication skills (verbal and written) and ability to present technical topics. Strong leadership skills and experience mentoring junior developers or leading small technical teams. Bachelor's or Master's in Computer Science, AI, Data Science, or a related discipline. Job Type: Full-time Pay: ₹600,000.00 - ₹1,500,000.00 per year Schedule: Day shift Monday to Friday Application Question(s): 1. Are you able to commute daily to Infopark, Koratty, Thrissur? (Yes/No) 2. How many years of total IT experience do you have? (Numeric) 3. How many years of experience do you have in AI/ML development? (Numeric) 4. How many years of experience do you have working with Large Language Models (LLMs)? (Numeric) 5. Are you proficient in Python? (Yes/No) 6. Have you used frameworks like TensorFlow, PyTorch, or Hugging Face? (Yes/No) 7. Have you deployed AI/ML models to production environments? (Yes/No) 8. Have you worked with cloud platforms like AWS, Azure, or GCP? (Yes/No) * 9. Do you have professional-level proficiency in English? (Yes/No) 10. What is your current notice period in days? (Numeric) 11. What is your expected salary in LPA? (Numeric) 12. What is your current or last drawn salary in LPA? (Numeric) Work Location: In person

Senior AI Engineer Location: Infopark, Thrissur, Kerala Employment Type: Full-Time Experience Required: Minimum 5 Years providing AI Solutions, including expertise in ML/DL Projects About Us JK Lucent is a growing IT services provider headquartered in Melbourne, Australia, with an operations centre at Infopark, Thrissur, Kerala. We specialize in Software Development, Software Testing, Game Development, RPA, Data Analytics, and AI solutions. At JK Lucent, we are driven by innovation and committed to delivering cutting-edge technology services that solve real-world problems and drive digital transformation. About the Role We are looking for a highly skilled and experienced Senior AI Engineer to lead the development and deployment of advanced AI systems. This role requires deep expertise in Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs). The successful candidate will work on complex AI initiatives, contribute to production-ready systems, and mentor junior engineers. A strong command of professional English and the ability to communicate technical concepts clearly is essential. Roles and Responsibilities · Design and develop scalable AI and ML models for real-world applications. · Build, fine-tune, and implement Large Language Models (LLMs) for use cases such as chatbots, summarization, and document intelligence. · Work with deep learning frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers. · Collaborate with cross-functional teams to translate business problems into AI solutions with necessary visualizations using tools like Tableau or Power BI. · Deploy models to production environments and implement monitoring and model retraining pipelines. · Stay up to date with the latest research and trends in AI, especially in LLMs and generative models. · Guide and mentor junior AI engineers, reviewing code and providing technical leadership. · Contribute to technical documentation, architecture design, and solution strategies. · Ensure models are developed and used ethically and comply with data privacy standards.  Requirements · Minimum 5 years of experience in AI/ML development with hands-on expertise in model design, development, and deployment. · Strong experience working with LLMs and Generative AI tools such as Hugging Face Hub, LangChain, Haystack, LLaMA, GPT, BERT, and T5. · Proficiency in Python and ML/DL libraries such as TensorFlow, PyTorch, XGBoost, scikit-learn, and Hugging Face Transformers. · Solid understanding of mathematics, statistics, and applied data science principles. · Experience deploying models using Docker, FastAPI, MLflow, or similar tools. · Familiarity with cloud platforms (AWS, Azure, or GCP) and their AI/ML services. · Demonstrated experience in working on end-to-end AI solutions in production environments. · Excellent English communication skills (verbal and written) and ability to present technical topics. · Strong leadership skills and experience mentoring junior developers or leading small technical teams. · Bachelor's or Master's in Computer Science, AI, Data Science, or a related discipline. Show more Show less

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. What Primary Responsibilities: Business Knowledge: Capable of understanding the requirements for the entire project (not just own features) Capable of working closely with PMG during the design phase to drill down into detailed nuances of the requirements Has the ability and confidence to question the motivation behind certain requirements and work with PMG to refine them. Design: Can design and implement machine learning models and algorithms Can articulate and evaluate pros/cons of different AI/ML approaches Can generate cost estimates for model training and deployment Coding/Testing: Builds and optimizes machine learning pipelines Knows & brings in external ML frameworks and libraries Consistently avoids common pitfalls in model development and deployment How Quality: Solves cross-functional problems using data-driven approaches Identifies impacts/side effects of models outside of immediate scope of work Identifies cross-module issues related to data integration and model performance Identifies problems predictively using data analysis Productivity: Capable of working on multiple AI/ML projects simultaneously and context switching between them Process: Enforces process standards for model development and deployment. Independence: Acts independently to determine methods and procedures on new or special assignments Prioritizes large tasks and projects effectively Agility: Release Planning: Works with the PO to do high-level release commitment and estimation Works with PO on defining stories of appropriate size for model development Agile Maturity: Able to drive the team to achieve a high level of accomplishment on the committed stories for each iteration Shows Agile leadership qualities and leads by example WITH Team Work: Capable of working with development teams and identifying the right division of technical responsibility based on skill sets. Capable of working with external teams (e.g., Support, PO, etc.) that have significantly different technical skill sets and managing the discussions based on their needs Initiative: Capable of creating innovative AI/ML solutions that may include changes to requirements to create a better solution Capable of thinking outside-the-box to view the system as it should be rather than only how it is Proactively generates a continual stream of ideas and pushes to review and advance ideas if they make sense Takes initiative to learn how AI/ML technology is evolving outside the organization Takes initiative to learn how the system can be improved for the customers Should make problems open new doors for innovations Communication: Communicates complex AI/ML concepts internally with ease Accountability: Well versed in all areas of the AI/ML stack (data preprocessing, model training, evaluation, deployment, etc.) and aware of all components in play Leadership: Disagree without being disagreeable Use conflict as a way to drill deeper and arrive at better decisions Frequent mentorship Builds ad-hoc cross-department teams for specific projects or problems Can achieve broad scope 'buy in' across project teams and across departments Takes calculated risks Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications B.E/B.Tech/MCA/MSc/MTech (Minimum 16 years of formal education, Correspondence courses are not relevant) 5+ years of experience working on multiple layers of technology Experience deploying and maintaining ML models in production Experience in Agile teams Experience with one or more data-oriented workflow orchestration frameworks (Airflow, KubeFlow etc.) Working experience or good knowledge of cloud platforms (e.g., Azure, AWS, OCI) Ability to design, implement, and maintain CI/CD pipelines for MLOps and DevOps function Familiarity with traditional software monitoring, scaling, and quality management (QMS) Knowledge of model versioning and deployment using tools like MLflow, DVC, or similar platforms Familiarity with data versioning tools (Delta Lake, DVC, LakeFS, etc.) Demonstrate hands-on knowledge of OpenSource adoption and use cases Good understanding of Data/Information security Proficient in Data Structures, ML Algorithms, and ML lifecycle Product/Project/Program Related Tech Stack: Machine Learning Frameworks: Scikit-learn, TensorFlow, PyTorch Programming Languages: Python, R, Java Data Processing: Pandas, NumPy, Spark Visualization: Matplotlib, Seaborn, Plotly Familiarity with model versioning tools (MLFlow, etc.) Cloud Services: Azure ML, AWS SageMaker, Google Cloud AI GenAI: OpenAI, Langchain, RAG etc. Demonstrate good knowledge in Engineering Practices Demonstrates excellent problem-solving skills Proven excellent verbal, written, and interpersonal communication skills At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission. Show more Show less

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. What Primary Responsibilities: Business Knowledge: Capable of understanding the requirements for the entire project (not just own features) Capable of working closely with PMG during the design phase to drill down into detailed nuances of the requirements Has the ability and confidence to question the motivation behind certain requirements and work with PMG to refine them. Design: Can design and implement machine learning models and algorithms Can articulate and evaluate pros/cons of different AI/ML approaches Can generate cost estimates for model training and deployment Coding/Testing: Builds and optimizes machine learning pipelines Knows & brings in external ML frameworks and libraries Consistently avoids common pitfalls in model development and deployment How Quality: Solves cross-functional problems using data-driven approaches Identifies impacts/side effects of models outside of immediate scope of work Identifies cross-module issues related to data integration and model performance Identifies problems predictively using data analysis Productivity: Capable of working on multiple AI/ML projects simultaneously and context switching between them Process: Enforces process standards for model development and deployment. Independence: Acts independently to determine methods and procedures on new or special assignments Prioritizes large tasks and projects effectively Agility: Release Planning: Works with the PO to do high-level release commitment and estimation Works with PO on defining stories of appropriate size for model development Agile Maturity: Able to drive the team to achieve a high level of accomplishment on the committed stories for each iteration Shows Agile leadership qualities and leads by example WITH Team Work: Capable of working with development teams and identifying the right division of technical responsibility based on skill sets. Capable of working with external teams (e.g., Support, PO, etc.) that have significantly different technical skill sets and managing the discussions based on their needs Initiative: Capable of creating innovative AI/ML solutions that may include changes to requirements to create a better solution Capable of thinking outside-the-box to view the system as it should be rather than only how it is Proactively generates a continual stream of ideas and pushes to review and advance ideas if they make sense Takes initiative to learn how AI/ML technology is evolving outside the organization Takes initiative to learn how the system can be improved for the customers Should make problems open new doors for innovations Communication: Communicates complex AI/ML concepts internally with ease Accountability: Well versed in all areas of the AI/ML stack (data preprocessing, model training, evaluation, deployment, etc.) and aware of all components in play Leadership: Disagree without being disagreeable Use conflict as a way to drill deeper and arrive at better decisions Frequent mentorship Builds ad-hoc cross-department teams for specific projects or problems Can achieve broad scope 'buy in' across project teams and across departments Takes calculated risks Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications B.E/B.Tech/MCA/MSc/MTech (Minimum 16 years of formal education, Correspondence courses are not relevant) 4+ years of experience working on multiple layers of technology Experience deploying and maintaining ML models in production Experience in Agile teams Experience with one or more data-oriented workflow orchestration frameworks (Airflow, KubeFlow etc.) Working experience or good knowledge of cloud platforms (e.g., Azure, AWS, OCI) Ability to design, implement, and maintain CI/CD pipelines for MLOps and DevOps function Familiarity with traditional software monitoring, scaling, and quality management (QMS) Knowledge of model versioning and deployment using tools like MLflow, DVC, or similar platforms Familiarity with data versioning tools (Delta Lake, DVC, LakeFS, etc.) Demonstrate hands-on knowledge of OpenSource adoption and use cases Good understanding of Data/Information security Proficient in Data Structures, ML Algorithms, and ML lifecycle Product/Project/Program Related Tech Stack: Machine Learning Frameworks: Scikit-learn, TensorFlow, PyTorch Programming Languages: Python, R, Java Data Processing: Pandas, NumPy, Spark Visualization: Matplotlib, Seaborn, Plotly Familiarity with model versioning tools (MLFlow, etc.) Cloud Services: Azure ML, AWS SageMaker, Google Cloud AI GenAI: OpenAI, Langchain, RAG etc. Demonstrate good knowledge in Engineering Practices Demonstrates excellent problem-solving skills Proven excellent verbal, written, and interpersonal communication skills At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission. 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

Responsibilities Manage Data: Extract, clean, and structure both structured and unstructured data. Coordinate Pipelines: Utilize tools such as Airflow, Step Functions, or Azure Data Factory to orchestrate data workflows. Deploy Models: Develop, fine-tune, and deploy models using platforms like SageMaker, Azure ML, or Vertex AI. Scale Solutions: Leverage Spark or Databricks to handle large-scale data processing tasks. Automate Processes: Implement automation using tools like Docker, Kubernetes, CI/CD pipelines, MLFlow, Seldon, and Kubeflow. Collaborate Effectively: Work alongside engineers, architects, and business stakeholders to address and resolve real-world problems efficiently. Qualifications 3+ years of hands-on experience in MLOps (4-5 years of overall software development experience). Extensive experience with at least one major cloud provider (AWS, Azure, or GCP). Proficiency in using Databricks, Spark, Python, SQL, TensorFlow, PyTorch, and Scikit-learn. Expertise in debugging Kubernetes and creating efficient Dockerfiles. Experience in prototyping with open-source tools and scaling solutions effectively. Strong analytical skills, humility, and a proactive approach to problem-solving. Preferred Qualifications Experience with SageMaker, Azure ML, or Vertex AI in a production environment. Commitment to writing clean code, creating clear documentation, and maintaining concise pull requests. Skills: sql,kubeflow,spark,docker,databricks,ml,gcp,mlflow,kubernetes,aws,pytorch,azure,ci/cd,tensorflow,scikit-learn,seldon,python,mlops 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 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

JOB DESCRIPTION About KPMG in India KPMG entities in India are professional services firm(s). These Indian member firms are affiliated with KPMG International Limited. KPMG was established in India in August 1993. Our professionals leverage the global network of firms, and are conversant with local laws, regulations, markets and competition. KPMG has offices across India in Ahmedabad, Bengaluru, Chandigarh, Chennai, Gurugram, Jaipur, Hyderabad, Jaipur, Kochi, Kolkata, Mumbai, Noida, Pune, Vadodara and Vijayawada. KPMG entities in India offer services to national and international clients in India across sectors. We strive to provide rapid, performance-based, industry-focused and technology-enabled services, which reflect a shared knowledge of global and local industries and our experience of the Indian business environment. QUALIFICATIONS • 3-5 years of hands-on experience in software development, with a focus on AI/ML, NLP, DL. Strong knowledge of AI/ML algorithms, Recommendation systems, Reinforcement Learning, Gen AI and AI Agents. Proficient in any one of the programming languages like Python or R, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc., with a strong understanding of AI compliance. Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure or GCP/On-premise hosting) . Well-versed with various AI/ML libraries for managing Bias, Variance etc. Experience in FastAPI. Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes, OpenShift Having knowledge or an understanding of Open Source Tools such as MLFlow and Fairlearn. Having an understanding of Gen AI prompt engineering techniques such as N-Shot, Chain of thoughts, Cove, etc. Ability to stay updated with the latest AI/ML security trends and technologies. Equal employment opportunity information KPMG India has a policy of providing equal opportunity for all applicants and employees regardless of their color, caste, religion, age, sex/gender, national origin, citizenship, sexual orientation, gender identity or expression, disability or other legally protected status. KPMG India values diversity and we request you to submit the details below to support us in our endeavor for diversity. Providing the below information is voluntary and refusal to submit such information will not be prejudicial to you.

Working at Freudenberg: "We will wow your world!" This is our promise. As a global technology group, we not only make the world cleaner, healthier and more comfortable, but also offer our 52,000 employees a networked and diverse environment where everyone can thrive individually. Be surprised and experience your own wow moments. Klüber Lubrication, a company of the Freudenberg Group, is the global leader in speciality lubrication with manufacturing operations in North and South America, Europe and Asia, subsidiaries in more than 30 different countries and distribution partners in all regions of the world, supported by our HQs in Germany. We are passionate about innovative tribological solutions that help our customers to be successful. We supply products and services, many of them customized, in almost all industries from automotive to the wind energy markets. Some of your Benefits Diversity & Inclusion Health Insurance Personal Development Safe Environment Sustainability & Social Commitment Bangalore On-Site Klüber Lubrication India Pvt. Ltd. You support our team as STATISTICAL ANALYTICS ENGINEER (F/M/D) Responsibilities Performs projects in statistics, data science and artificial intelligence in the technical field of KL under the guidance of experts, evaluates and comments on results Implements data processes and data products into operations and works on their operation and optimization Coordinates regularly with experts in statistics, data science and artificial intelligence at KL Maintains a balance between effort (time, cost) and expected benefit of incoming requests Contributes ideas for KL-relevant developments and methods, especially in the field of data analysis and artificial intelligence, and implements them as needed Supports the improvement and automation of processes/workflows in own & adjacent work areas through statistical methods and evaluations Works on cross-functional project teams and projects with external partners Keeps own expertise up to date (self-study, external training, meetings, specialist groups) Supports technical colleagues in the introduction, use and quality assurance of data analysis tools Presents contributions to statistics and data science in the context of Klüber internal and customer training Qualifications Engineering Graduate /Masters in Chemistry, Physics or equivalent degree Overall 7 -10 years of experience in data modelling, analysis and visualization in manufacturing or industrial environment. Completed higher education in science, focus on chemistry, physics, mathematics or related discipline Strong experience in methods for processing, evaluating and modeling data In depth programming knowledge with a focus on data science and data engineering, preferably in Python Experience using cheminformatics, materials informatics, generative AI and machine learning Experience in developing interactive data applications with frameworks like Shiny, Dash or streamlit good knowledge of relational data (SQL), experience in tools like JupyterLab, Gitlab, Airflow, MLFlow, knowledge of chemical analysis and organic chemistry The Freudenberg Group is an equal opportunity employer that is committed to diversity and inclusion. Employment opportunities are available to all applicants and associates without regard to race, color, religion, creed, gender (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity or expression, national origin, ancestry, age, mental or physical disability, genetic information, marital status, familial status, sexual orientation, protected military or veteran status, or any other characteristic protected by applicable law. Additional Information Kausik Bose kausik.bose@klueber.com

Job Information Number of Positions 1 Industry Engineering Date Opened 06/09/2025 Job Type Permanent Work Experience 2-3 years City Bangalore State/Province Karnataka Country India Zip/Postal Code 560037 Location Bangalore About Us CloudifyOps is a company with DevOps and Cloud in our DNA. CloudifyOps enables businesses to become more agile and innovative through a comprehensive portfolio of services that addresses hybrid IT transformation, Cloud transformation, and end-to-end DevOps Workflows. We are a proud Advance Partner of Amazon Web Services and have deep expertise in Microsoft Azure and Google Cloud Platform solutions. We are passionate about what we do. The novelty and the excitement of helping our customers accomplish their goals drives us to become excellent at what we do. Job Description Culture at CloudifyOps : Working at CloudifyOps is a rewarding experience! Great people, a work environment that thrives on creativity, and the opportunity to take on roles beyond a defined job description are just some of the reasons you should work with us. About the Role: We are seeking a proactive and technically skilled AI/ML Engineer with 2–3 years of experience to join our growing technology team. The ideal candidate will have hands-on expertise in AWS-based machine learning, Agentic AI, and Generative AI tools, especially within the Amazon AI ecosystem. You will play a key role in building intelligent, scalable solutions that address complex business challenges. Key Responsibilities: 1. AWS-Based Machine Learning Develop, train, and fine-tune ML models on AWS SageMaker, Bedrock, and EC2. Implement serverless ML workflows using Lambda, Step Functions, and EventBridge. Optimize models for cost/performance using AWS Inferentia/Trainium. 2. MLOps & Productionization Build CI/CD pipelines for ML using AWS SageMaker Pipelines, MLflow, or Kubeflow. Containerize models with Docker and deploy via AWS EKS/ECS/Fargate. Monitor models in production using AWS CloudWatch, SageMaker Model Monitor. 3. Agentic AI Development Design autonomous agent systems (e.g., AutoGPT, BabyAGI) for task automation. Integrate multi-agent frameworks (LangChain, AutoGen) with AWS services. Implement RAG (Retrieval-Augmented Generation) for agent knowledge enhancement. 4. Generative AI & LLMs Fine-tune and deploy LLMs (GPT-4, Claude, Llama 2/3) using LoRA/QLoRA. Build Generative AI apps (chatbots, content generators) with LangChain, LlamaIndex. Optimize prompts and evaluate LLM performance using AWS Bedrock/Amazon Titan. 5. Collaboration & Innovation Work with cross-functional teams to translate business needs into AI solutions. Collaborate with DevOps and Cloud Engineering teams to develop scalable, production-ready AI systems. Stay updated with cutting-edge AI research (arXiv, NeurIPS, ICML). 5. Governance & Documentation Implement model governance frameworks to ensure ethical AI/ML deployments. Design reproducible ML pipelines following MLOps best practices (versioning, testing, monitoring). Maintain detailed documentation for models, APIs, and workflows (Markdown, Sphinx, ReadTheDocs). Create runbooks for model deployment, troubleshooting, and scaling. Technical Skills Programming: Python (PyTorch, TensorFlow, Hugging Face Transformers). AWS: SageMaker, Lambda, ECS/EKS, Bedrock, S3, IAM. MLOps: MLflow, Kubeflow, Docker, GitHub Actions/GitLab CI. Generative AI: Prompt engineering, LLM fine-tuning, RAG, LangChain. Agentic AI: AutoGPT, BabyAGI, multi-agent orchestration. Data Engineering: SQL, PySpark, AWS Glue/EMR. Soft Skills Strong problem-solving and analytical thinking. Ability to explain complex AI concepts to non-technical stakeholders. What We’re Looking For Bachelor’s/Master’s in CS, AI, Data Science, or related field. 2-3 years of industry experience in AI/ML engineering. Portfolio of deployed ML/AI projects (GitHub, blog, case studies). Good to have an AWS Certified Machine Learning Specialty certification. Why Join Us? Innovative Projects: Work on cutting-edge AI applications that push the boundaries of technology. Collaborative Environment: Join a team of passionate engineers and researchers committed to excellence. Career Growth: Opportunities for professional development and advancement in the rapidly evolving field of AI. Equal opportunity employer CloudifyOps is proud to be an equal opportunity employer with a global culture that embraces diversity. We are committed to providing an environment free of unfair discrimination and harassment. We do not discriminate based on age, race, color, sex, religion, national origin, disability, pregnancy, marital status, sexual orientation, gender reassignment, veteran status, or other protected category.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Position Name ML Developer Taleo ID Position Level Staff Employment Type Permanent Number of Openings 1 Work Location Kochi, Chennai , Noida , Bangalore , Pune , Kolkata , TVM Position Details As part of EY GDS Assurance Digital, you will be responsible for leveraging advanced machine learning techniques to develop innovative, high-impact models and solutions that drive growth and deliver significant business value. You will be helping EY’s sector and service line professionals by developing analytics enabled solutions, integrating data science activities with business relevant aspects to gain insight from data. This is a full-time Machine Learning Developer role, responsible for building and deploying robust machine learning models to solve real-world business problems. You will be working on the entire ML lifecycle, including data analysis, feature engineering, model training, evaluation, and deployment. Requirements (including experience, skills and additional qualifications) A bachelor’s degree (BE/BTech/MCA & MBA) in Computer Science, Engineering, Information Systems Management, Accounting, Finance or a related field with adequate industry experience. Technical skills requirements Develop and implement machine learning models, including regression, classification (e.g., XGBoost, Random Forest), and clustering techniques. Conduct exploratory data analysis (EDA) to uncover insights and trends within data sets. Apply dimension reduction techniques to improve model performance and interpretability. Utilize statistical models to design and implement effective business solutions. Evaluate and validate models to ensure robustness and reliability. Should have solid background in Python Familiarity with Time Series Forecasting . Basic experience with cloud platforms such as AWS, Azure, or GCP. Exposure to ML Ops tools and practices (e.g., MLflow, Airflow, Docker) is a plus Additional skill requirements:  Proficient at quickly understanding complex machine learning concepts and utilizing technology for tasks such as data modeling, analysis, visualization, and process automation. Skilled in selecting and applying the most suitable standards, methods, tools, and frameworks for specific ML tasks and use cases. Capable of collaborating effectively within cross-functional teams, while also being able to work independently on complex ML projects. Demonstrates a strong analytical mindset and systematic approach to solving machine learning challenges. Excellent communication skills, able to present complex technical concepts clearly to both technical and non-technical audiences. What we look for A Team of people with commercial acumen, technical experience, and enthusiasm to learn new things in this fast-moving environment. An opportunity to be a part of market-leading, multi-disciplinary team of 7200 + professionals, in the only integrated global assurance business worldwide. Opportunities to work with EY GDS Assurance practices globally with leading businesses across a range of industries What working at EY offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction, and advisory services, we’re using the finance products, expertise, and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities, and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. And with a commitment to hiring and developing the most passionate people, we’ll make our ambition to be the best employer by 2020 a reality. If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible. Join us in building a better working world. Apply now EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

Job description Location: Mumbai/ Bengaluru Experience: 3-5 years Industry: Banking / Financial Services (Mandatory) Why would you like to join us? TransOrg Analytics specializes in Data Science, Data Engineering and Generative AI, providing advanced analytics solutions to industry leaders and Fortune 500 companies across India, US, APAC and the Middle East. We leverage data science to streamline, optimize, and accelerate our clients' businesses. Visit at www.transorg.com to know more about us. What do we expect from you? Build and validate credit risk models , including application scorecards and behavior scorecards (B-score), aligned with business and regulatory requirements. Use advanced machine learning algorithms such as Logistic Regression, XGBoost , and Clustering to develop interpretable and high-performance models. Translate business problems into data-driven solutions using robust statistical and analytical methods. Collaborate with cross-functional teams including credit policy, risk strategy, and data engineering to ensure effective model implementation and monitoring. Maintain clear, audit-ready documentation for all models and comply with internal model governance standards. Track and monitor model performance, proactively suggesting recalibrations or enhancements as needed. What do you need to excel at? Writing efficient and scalable code in Python, SQL, and PySpark for data processing, feature engineering, and model training. Working with large-scale structured and unstructured data in a fast-paced, banking or fintech environment. Deploying and managing models using MLFlow, with a strong understanding of version control and model lifecycle management. Understanding retail banking products , especially credit card portfolios , customer behavior, and risk segmentation. Communicating complex technical outcomes clearly to non-technical stakeholders and senior management. Applying a structured problem-solving approach and delivering insights that drive business value. What are we looking for? Bachelors or masters degree in Statistics, Mathematics, Computer Science , or a related quantitative field. 3-5 years of experience in credit risk modelling , preferably in retail banking or credit cards. Hands-on expertise in Python, SQL, PySpark , and experience with MLFlow or equivalent MLOps tools. Deep understanding of machine learning techniques including Logistic Regression, XGBoost, and Clustering. Proven experience in developing Application Scorecards and behavior Scorecards using real-world banking data. Strong documentation and compliance orientation, with an ability to work within regulatory frameworks. Curiosity, accountability, and a passion for solving real-world problems using data. Cloud Knowledge, JIRA, GitHub(good to have) Show more Show less

Job Description Role: AI Engineer Employment Type: Full-Time, Permanent Location: On-site, Bengaluru Vacancies: Multiple Positions Company Overview EmployAbility.AI is an AI-driven career enablement platform dedicated to transforming how individuals and organizations navigate the future of work. We are committed to democratizing access to meaningful employment by using advanced artificial intelligence, real-time labor market data, and intelligent career pathways to bridge the gap between skills and opportunities. Our platform empowers job seekers with personalized career insights, learning recommendations, and job-matching tools while enabling organizations to make smarter hiring and workforce development decisions. By aligning talent capabilities with market demand, we help create a more inclusive, adaptive, and future-ready workforce. At EmployAbility.AI, we’re not just building software—we’re building solutions that make employability equitable, data-driven, and scalable. Job Role: AI Engineer As an AI Engineer at EmployAbility.AI, you will be at the forefront of building intelligent systems that power the platform’s core functionality—from LLM-based recommendations to intelligent search and contextual assistants. You will develop and deploy state-of-the-art AI models and pipelines using LLMs , LangChain , and Retrieval-Augmented Generation (RAG) to deliver impactful, real-world solutions. You will work closely with a cross-functional team of developers, data scientists, and product managers to create scalable, production-ready AI features that enhance user experiences and drive measurable value across industries and regions. Key Responsibilities Design and develop AI-driven features including conversational agents, recommendation engines, and smart search using LLMs. Build and integrate LangChain-based applications that leverage RAG pipelines for improved reasoning and contextual understanding. Fine-tune, evaluate, and optimize transformer models (BERT, GPT, LLaMA, etc.) for domain-specific use cases. Work with unstructured and semi-structured data (e.g., resumes, job descriptions, labor market datasets). Develop embedding-based search using tools like FAISS , Pinecone , or Weaviate . Collaborate with backend and frontend teams to integrate AI services via scalable APIs. Perform data preprocessing, feature engineering, and model evaluation. Monitor performance of deployed models and iterate based on feedback and metrics. Participate in prompt engineering, experiment tracking, and continuous optimization of AI systems. Stay updated on the latest trends in AI/ML and contribute to internal knowledge sharing. Education Requirements B.Tech/B.E, M.Tech, MCA, M.Sc, MS, or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Core Technical Skills – AI Engineering Large Language Models & NLP Experience with LLMs and transformer-based architectures (e.g., GPT, BERT, LLaMA). Hands-on with LangChain framework and RAG (Retrieval-Augmented Generation) workflows. Proficiency in prompt engineering , embedding models, and semantic search. Experience using Hugging Face Transformers , OpenAI API , or open-source equivalents. Vector Stores & Knowledge Retrieval Experience with FAISS , Pinecone , or Weaviate for similarity search. Implementation of document chunking, embedding pipelines, and vector indexing. ML/AI Development Strong skills in Python and ML libraries (PyTorch, TensorFlow, Scikit-learn). Familiar with NLP tasks like named entity recognition, text classification, and summarization. Experience with API development and deploying AI models into production environments. Tooling & Development Practices Version control with Git , collaborative workflows via GitHub Experiment tracking with MLflow , Weights & Biases , or equivalent API testing tools (Postman, Swagger), and JSON schema validation Use of Jupyter notebooks for experimentation and prototyping Deployment & DevOps (Basic Understanding) Containerization using Docker , basic orchestration knowledge is a plus Cloud environments: familiarity with AWS , GCP , or Azure CI/CD workflows (GitHub Actions, Jenkins) Monitoring tools for model performance and error tracking (Sentry, Prometheus, etc.) Soft Skills & Work Habits Strong problem-solving and analytical thinking Ability to work cross-functionally with technical and non-technical teams Clear and concise communication of complex AI concepts Team collaboration and willingness to mentor peers or juniors Agile/Scrum practices using tools like Jira, Trello, and Confluence Bonus Skills (Good to Have) TypeScript or JavaScript for frontend or integration work Knowledge of GraphQL , chatbot development , or multi-modal AI Familiarity with AutoML , RLHF , or explainable AI Experience with knowledge graphs , ontologies , or custom taxonomies Show more Show less

We are seeking a highly skilled and experienced Senior AI Engineer to lead the design, development, and deployment of cutting-edge AI/ML solutions across our products and platforms. As a senior member of the team, you will be responsible for solving complex problems using AI technologies, mentoring junior engineers, and collaborating cross-functionally with product, data, and engineering teams to deliver scalable and impactful AI-driven features. Key Responsibilities: Design and develop advanced machine learning models and deep learning architectures for real-world problems. Lead AI/ML system design, including data pipelines, model training workflows, evaluation strategies, and deployment frameworks. Conduct research and experimentation with new algorithms, tools, and technologies to enhance the company's AI capabilities. Collaborate with product managers, data scientists, and software engineers to translate business requirements into AI solutions. Mentor and guide junior AI engineers and data scientists, fostering best practices in coding, experimentation, and model deployment. Optimize and monitor model performance in production, including addressing issues of bias, drift, and latency. Stay current with AI research, tools, and industry trends, and bring innovative ideas into the team. Contribute to technical strategy and help define the roadmap for AI initiatives. Requirements Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field (Ph.D. preferred). 5+ years of experience in AI/ML engineering with a strong portfolio of production-level projects. Deep knowledge of machine learning and deep learning algorithms (e.g., CNNs, RNNs, Transformers, LLMs). Proficient in Python and libraries such as TensorFlow, PyTorch, Scikit-learn, and Hugging Face. Strong experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow) and cloud platforms (e.g., AWS, GCP, Azure). Experience in deploying and maintaining models in production at scale. Strong understanding of data structures, algorithms, and software engineering principles. Excellent problem-solving skills and communication abilities. Show more Show less

It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business. Job Profile - Senior Engineer Python + AWS cloud Exp - 4-7 yrs Job Location – Bangalore We’re looking for a top-notch Software Engineer who always sweats the small stuff and cares about impeccable code. If you always strive towards a sustainable, scalable and secure code for every single application you develop, while keeping in mind the customer needs, then you are what we are looking for. You’ll get the chance to work with experienced engineers across our enterprise with a chance to move across varying automation technologies in the future. As Python developers in AI team, you will have the opportunity to work on multiple complex assignments like physics based complex models, lambda functions, automation pipelines, object-oriented programming, etc. Responsibilities Analyze and translate business requirements into scalable and resilient design. Own parts of the application and continuously improve them in an agile environment. Create high quality maintainable products and applications using best engineering practices. Pair with other developers and share design philosophy and goals across the team. Work in cross functional teams (DevOps, Data, UX, Testing etc.). Build and manage fully automated build/test/deployment environments. Ensure high availability and provide quick turnaround to production issues. Contribute to the design of useful, usable, and desirable products in a team environment. Adapt to new programming languages, methodologies, platforms, and frameworks to support the business needs. Qualifications Degree in computer science or a similar field. Four or more years of experience in architecting, designing, developing, and implementing cloud solutions on AWS and/or Azure platforms. Technologies: Python, Azure, AWS, MLFlow, Kubernetes, Terraform, AWS Sage maker, Lambda, Step Function. Development experience with configuration management tools (Terraform, Ansible, CloudFormation). Developing and maintaining continuous integration and continuous deployment pipelines – Jenkins Groovy scripts. Developing containerized solutions and orchestration (Docker, Kubernetes, ECS, ECR) Experience of server less architecture, cloud computing, cloud native application and scalability etc. Understanding of core cloud concepts like Infra as code, IaaS, PaaS and SaaS. Relevant certification of Azure or AWS preferred. Troubleshooting and analytical skills. Knowledge of AI & ML technologies, as well as ML model management context Strong verbal & written communication: should be able to articulate concisely & clearly. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us! Not the right fit? Let us know you're interested in a future opportunity by clicking Introduce Yourself in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest! Show more Show less