AI Ops Engineer

Job Description Role Summary: Builds, trains and tunes machine learning models. Translates data science experiments into scalable, production-ready ML solutions. Key Responsibilities Translate data science prototypes into production-grade ML services and pipelines. Build training and inference code with reproducibility, versioning, and automated testing. Implement scalable model serving (online/offline), batching, and latency/throughput optimization. Integrate model lifecycle tooling (tracking, registry, deployment automation, monitoring). Collaborate with Data Engineering on feature pipelines and data contracts. Own production health: drift detection, performance regression, rollback strategies, and incident response. Required Qualifications 5+ years software engineering with 2+ years shipping ML models to production. Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch). Experience with containers and orchestration (Docker/Kubernetes) and API development. Understanding of ML system design (data leakage, training-serving skew, drift). CI/CD and DevOps practices applied to ML workloads (MLOps). Experience with CI/CD and DevOps practices applied to ML (MLOps) Salary Range: $100,000 – $120,000 a year Benefits Discretionary Annual Incentive. Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans. Family Support: Maternal & Parental Leaves. Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement. Time Off: Vacation, Time Off, Sick Leave & Holidays. Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing. Qualifications: BACHELOR OF COMPUTER SCIENCE #J-18808-Ljbffr Tata Consultancy Services