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Machine Learning Engineer at Virtusa UK Limited

Minneapolis, Minnesota, United States -

Full Time

Start Date

Immediate

Expiry Date

12 Jun, 26

Salary

0.0

Posted On

14 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, TensorFlow, PyTorch, Docker, Kubernetes, API Development, MLOps, CI/CD, DevOps, Feature Stores, Model Registries, Model Monitoring, GPU Optimization, Distributed Training, Responsible AI

Industry

IT Services and IT Consulting

Description

Role Summary:- Builds, trains and tunes machine learning models. Translates data science experiments into scalable, production-ready ML solutions. Ker 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 Qualification:- - 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). 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.

Responsibilities

The role involves building, training, and tuning machine learning models, translating data science experiments into scalable, production-ready ML solutions, and implementing scalable model serving and optimization.