Senior ML Engineer - ML Ops Framework
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The role
You will build, maintain, and improve ML frameworks that cover the full lifecycle from ideation, training, and validation to model comparison and deployment.
Contribute to cloud tooling and infrastructure with Terraform, AWS managed services, EKS, and Ray to scale experiments.
Lead data engineering work including Parquet processing (PyArrow, Daft, Pandas), vector databases (LanceDB), and MCAP/ROS.
Develop the ML development pipeline using Python, Ray, PyTorch, Lightning, and Gymnasium.
Implement logging, experiment tracking, model registry and lineage, and create visual dashboards using tools like Tableau, Voxel51, or rerun.
Ideal candidates have 6+ years (3+ with Master) of experience, production ML experience, Ray evangelism, and comfort with scaling ML systems; edge deployment optimization is a plus and collaborating with users is valued.
Contribute to cloud tooling and infrastructure with Terraform, AWS managed services, EKS, and Ray to scale experiments.
Lead data engineering work including Parquet processing (PyArrow, Daft, Pandas), vector databases (LanceDB), and MCAP/ROS.
Develop the ML development pipeline using Python, Ray, PyTorch, Lightning, and Gymnasium.
Implement logging, experiment tracking, model registry and lineage, and create visual dashboards using tools like Tableau, Voxel51, or rerun.
Ideal candidates have 6+ years (3+ with Master) of experience, production ML experience, Ray evangelism, and comfort with scaling ML systems; edge deployment optimization is a plus and collaborating with users is valued.
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