Senior Machine Learning Engineer – GeoAI Platform

Wherobots is a company focused on building AI infrastructure for the physical world, and they are seeking a Senior Machine Learning Engineer to architect and operate their geospatial ML platform. The role involves designing and implementing high-throughput data pipelines, optimizing GPU inference, and ensuring production reliability for large-scale geospatial data workflows.

Responsibilities:

• Design and operate end-to-end ML pipelines : Build pipelines over massive raster archives such as Zarr and COG, from ingestion to feature generation to inference to publication
• Build high-throughput distributed pipelines : Use Ray (Datasets and actors) with careful control over I/O, compute overlap, and backpressure to keep clusters fully utilized
• Optimize GPU inference at scale : Tune PyTorch inference pipelines using batching, CUDA stream overlap, and memory-aware scheduling to maximize throughput per GPU
• Develop spatial data processing patterns : Implement tiling, overlapping windows, and accumulators that match the access patterns of spatial models
• Ensure production reliability : Build in retries, checkpointing, observability, and cost-efficient scaling so long-running global jobs are debuggable and resilient to failure
• Build reusable platform abstractions : Collaborate on abstractions that generalize across datasets, models, and product use cases so new workflows ship quickly
• Raise the bar : Provide technical leadership on architecture, engineering standards, and roadmap, and contribute to architecture and code reviews across the organization