Senior Machine Learning Engineer
Role summary
We are seeking a Senior Machine Learning Engineer to translate data science prototypes into production-grade ML services and pipelines. You will build robust training and inference code with reproducibility, versioning, and automated testing. The role involves implementing scalable model serving, optimizing for latency and throughput, and integrating model lifecycle tooling. You will collaborate with Data Engineering on feature pipelines and data contracts, and own production health, including drift detection, performance regression, rollback strategies, and incident response. This position requires strong Python skills, experience with ML frameworks like TensorFlow/PyTorch, and expertise in containers, orchestration, and API development.
- 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
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