Senior Machine Learning Engineer

Job Summary

To support the development of a large-scale geospatial ML platform, the full-time Senior Machine Learning Engineer will design and operate end-to-end ML pipelines, build high-throughput distributed pipelines, and optimize GPU inference at scale while working remotely or in-office in Bellevue or San Francisco.

Key responsibilities

• Design and operate end-to-end ML pipelines over massive raster archives, from ingestion to publication
• Build high-throughput distributed pipelines using Ray, ensuring optimal resource utilization
• Optimize GPU inference pipelines for maximum throughput through advanced scheduling and batching techniques

Required qualifications

• 5+ years of experience building distributed data or ML systems in production
• Strong hands-on experience with Ray, Spark, Dask, or similar distributed computing systems
• Deep understanding of performance tradeoffs across memory, I/O, serialization, and scheduling
• Production experience running GPU inference workloads at scale
• Proficiency in Python and the scientific Python stack (PyTorch, PyArrow, NumPy, Xarray)