Senior Machine Learning Engineer

What you'll do

• Build and own high-throughput data access and loading systems for GPU and TPU training fleets.
• Develop Python and Rust libraries and distributed pipelines for dataset access, transformation, and preparation.
• Support versioning, lineage, governance, framework integration, and production reliability across the ML data platform.

What they ask for

• 5+ years in machine learning infrastructure, distributed data systems, or a related field, and 5+ years building and shipping production data or ML infrastructure.
• Experience operating production systems, including monitoring, observability, on-call, and incident response.
• Strong Python skills and a systems language; Rust is strongly preferred, with C++ or Go acceptable.
• Familiarity with columnar/lakehouse formats and hands-on I/O performance engineering; B.S., M.S., or Ph.D. in a relevant field, or equivalent practical experience.

Nice to have

• Deep experience with dataset access in PyTorch, JAX, or TensorFlow; distributed ML data-loading frameworks.
• Experience feeding large GPU/TPU fleets, data lineage/governance systems, data-processing internals, or Docker and Kubernetes.

Pay

$175,000 and $308,500 (base salary)

Tools

Python, Rust, C++, Go, Spark, Daft, PyTorch, JAX

AI focus

Build the data infrastructure supporting foundation-model and GenAI workloads, including dataset preparation and access for training and inference; model-building itself is not required.