ML Engineer-Minneapolis, MN

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Job Role - ML Engineer

Location - Minneapolis, MN (Onsite)

Can do Only W2. No C2C

Job Description

• 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."
• "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 feature stores, model registries, and model monitoring stacks.
• GPU optimization and distributed training experience.
• Experience with responsible AI toolkits and compliance requirements."
• Python, TensorFlow, PyTorch, Docker, REST APIs.

Best Regards

Monika G

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