MLOps Technical Architect

Greetings From TCS!!!\n\nTCS presents an Excellent opportunity for MLOps Technical Architect\nDesired Experience Range: 10 to 15+ Years\nLocation of Requirement: Bangalore\nRequired Skill: MLFlow, Docker, Kubernetes, PySpark, Azure databricks\n\nTechnical/Functional Skills:\n\nWe are seeking a Senior MLOps Engineer to design, build, and maintain robust machine learning infrastructure and deployment pipelines. This role will bridge the gap between data science and engineering, enabling scalable, reliable, and efficient ML systems in production environments.\nMLFlow, Docker, Kubernetes, PySpark, Azure databricks\nCI/CD Tools: Jenkins, GitHub, Azure DevOps\nMonitoring Tools: Prometheus, Grafana\nDatabases & Storage: SQL/postgresql databases, data lakes\n\nResponsibility of / Expectations from the Role:\nML Infrastructure & Pipeline Development\nDesign and implement end-to-end ML pipelines (data ingestion, preprocessing, training, validation, deployment)\nDevelop and maintain CI/CD pipelines for machine learning models\nBuild scalable infrastructure for model training, serving, and monitoring\nImplement version control for models, data, and code (MLOps practices)\n\nModel Deployment & Serving\nContainerize ML models using Docker and orchestrate with Kubernetes\nImplement model serving solutions (REST APIs, batch processing, real-time inference)\nOptimize model performance for production environments\nManage A/B testing and canary deployments for ML models\n\nMonitoring & Reliability\nImplement monitoring solutions for model performance, data drift, and system health\nCreate automated alerting systems for model degradation\nDesign and implement model retraining pipelines\nEnsure system reliability, scalability, and security of ML applications\n\nCollaboration & Best Practices\nWork closely with data scientists to productionize research models\nCollaborate with DevOps and software engineering teams\nEstablish MLOps best practices and standards\nDocument systems, processes, and architectures\n\nEducation: Ph.D/M.Tech/B.Tech in Computer Science, Electrical Engineering, Mechanical Engineering or related streams.\n\nTechnical Proficiency:\n>5 years in MLOps, DevOps, or ML engineering roles\nProven experience deploying and maintaining ML models in production\n\nProblem-Solving: Strong analytical and problem-solving skills with the ability to iterate quickly from experimentation to production-ready solutions.\n\nNote: We encourage you to register at www.tcs.com/careers for exploring an exciting career with TCS at the time of your application to TCS\n\nKindly Visit URL: https://ibegin.tcs.com/iBegin/register\na) Complete the online TCS application form (Very Important)\nb) Upload latest resume, Government ID proof (PAN CARD) and l\ntest passport Size Photo (white background is preferable) in the portal after registering.\n\nWarm Regards,\nShalini C – HR-TAG,\nTata Consultancy Services, India.