Staff ML Systems Engineer, Distributed Systems

FieldAI is a company that builds risk-aware, reliable, field-ready AI systems for robotics. They are seeking a Staff ML Systems Engineer to design and build distributed infrastructure that supports large-scale machine learning workflows, focusing on scalable systems for data processing and model training.

Responsibilities:

• Design and build scalable distributed machine learning pipelines across data processing, model training, evaluation, and post-processing workflows
• Architect distributed execution systems, including parallelization strategies, workload scheduling, resource allocation, and fault tolerance mechanisms
• Develop reusable abstractions, frameworks, and libraries that simplify distributed pipeline development
• Optimize performance across distributed CPU and GPU environments, improving throughput, utilization, and reliability
• Design systems that effectively manage data partitioning, memory utilization, serialization overhead, and compute efficiency
• Partner closely with ML engineers, data engineers, and infrastructure teams to productionize research workflows and enable large-scale model development
• Establish best practices and engineering standards for distributed machine learning infrastructure
• Evaluate and guide decisions around distributed computing frameworks, infrastructure technologies, and system design trade-offs
• Improve observability, debugging, monitoring, and operational tooling for distributed systems at scale