Machine Learning Engineer (MLOps Production ML)
Job Location:
Hartford, CT - USA
Monthly Salary:
Posted on:
Vacancies:
Job Summary
Job Description:
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Translate data science prototypes into production-grade ML services and pipelines.
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Build training and inference code with reproducibility versioning and automated testing.
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Implement scalable model serving (online/offline) batching and latency/throughput optimization.
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Integrate model lifecycle tooling (tracking registry deployment automation monitoring).
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Collaborate with Data Engineering on feature pipelines and data contracts.
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Own production health: drift detection performance regression rollback strategies and incident response.
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5 years software engineering with 2 years shipping ML models to production.
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Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).
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Experience with containers and orchestration (Docker/Kubernetes) and API development.
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Understanding of ML system design (data leakage training-serving skew drift).
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CI/CD and DevOps practices applied to ML workloads (MLOps).
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Experience with feature stores model registries and model monitoring stacks.
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GPU optimization and distributed training experience.
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Experience with responsible AI toolkits and compliance requirements.
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Python TensorFlow PyTorch Docker REST APIs
