Senior, ML Engineer - ML Ops Framework
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The role
As a Senior ML Engineer, you will build, maintain, and improve a scalable ML framework that enables end-to-end ML experimentation, training, validation, and deployment at scale.
You will own cloud tooling and infrastructure using Terraform, AWS Managed Services, EKS, and Ray to enable reproducible ML workloads.
You will drive data operations with Parquet processing (PyArrow, Daft, Pandas), vector databases (LanceDB), and standards for MCAP/ROS.
You will contribute to the ML development pipeline with Python, Ray, PyTorch, Lightning, and Gymnasium, ensuring robust experimentation and model iteration.
You will implement and maintain logging, experiment tracking, model registry, and lineage, plus dashboards for visibility (Tableau, Voxel51, or Rerun).
Collaboration with users and teams to understand needs and deliver scalable, production-ready ML systems that can run at fleet scale.
You will own cloud tooling and infrastructure using Terraform, AWS Managed Services, EKS, and Ray to enable reproducible ML workloads.
You will drive data operations with Parquet processing (PyArrow, Daft, Pandas), vector databases (LanceDB), and standards for MCAP/ROS.
You will contribute to the ML development pipeline with Python, Ray, PyTorch, Lightning, and Gymnasium, ensuring robust experimentation and model iteration.
You will implement and maintain logging, experiment tracking, model registry, and lineage, plus dashboards for visibility (Tableau, Voxel51, or Rerun).
Collaboration with users and teams to understand needs and deliver scalable, production-ready ML systems that can run at fleet scale.
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