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Machine Learning Engineer (MLOps / Production ML Engineer)
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Info Dinamica Inc
Hartford, CT (In Person)
Full-Time
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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.