Virtusa is hiring: Machine Learning Engineer in Minneapolis
Virtusa, Minneapolis, MN, United States
Job Description - Machine Learning Engineer (252507)
Job Description
Description
Overview
Role Summary: Builds, trains and tunes machine learning models. Translates data science experiments into scalable, production-ready ML solutions.
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.
Collaborate with Data Engineering on feature pipelines and data contracts.
Own production health: drift detection, performance regression, rollback strategies, and incident response.
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).
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.
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Job Description
Description
Overview
Role Summary: Builds, trains and tunes machine learning models. Translates data science experiments into scalable, production-ready ML solutions.
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.
Collaborate with Data Engineering on feature pipelines and data contracts.
Own production health: drift detection, performance regression, rollback strategies, and incident response.
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).
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.
#J-18808-Ljbffr