AI Ops Engineer

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

TCS Employee Benefits Summary:

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 & amp; Training Reimbursement.

Time Off: Vacation, Time Off, Sick Leave & Holidays.

Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

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