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).
Preferred / Nice
to Have
- Experience with feature stores, model registries, and model monitoring stacks.
- GPU optimization and distributed training experience.
- Experience with responsible AI toolkits and compliance requirements.
Salary Range:
$100,000
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. #LI-SP1