Senior ML Engineer - ML Ops Framework
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The role
You will build, maintain, and improve our ML frameworks to support end-to-end ML experimentation, training, validation, and model deployment.
Own cloud tooling and distributed compute using Terraform, AWS Managed Services, EKS, and Ray to scale ML workloads.
Lead data ops including Parquet processing (PyArrow, Daft, Pandas), vector databases (LanceDB), and MCAP/ROS integration.
Develop ML development pipelines with Python, Ray, PyTorch, Lightning, and Gymnasium, ensuring reproducibility through logging, experiment tracking, and a robust model registry and lineage.
Create visualization and dashboards (Tableau, voxel51, rerun) to monitor experiments and enable data-driven decision making for users across teams.
Partner with stakeholders to deliver a scalable ML platform, promote best practices, and consider edge deployment optimizations when applicable.
Own cloud tooling and distributed compute using Terraform, AWS Managed Services, EKS, and Ray to scale ML workloads.
Lead data ops including Parquet processing (PyArrow, Daft, Pandas), vector databases (LanceDB), and MCAP/ROS integration.
Develop ML development pipelines with Python, Ray, PyTorch, Lightning, and Gymnasium, ensuring reproducibility through logging, experiment tracking, and a robust model registry and lineage.
Create visualization and dashboards (Tableau, voxel51, rerun) to monitor experiments and enable data-driven decision making for users across teams.
Partner with stakeholders to deliver a scalable ML platform, promote best practices, and consider edge deployment optimizations when applicable.
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