Senior ML Systems Architect for Field-Ready Pipelines

Field Ai; Irvine (CA); On-site; USD 195,000 - 230,000; Full time

Benefits offered by this job

Equity participation

Competitive compensation

Benefits

Job summary

FieldAI in Irvine is seeking a Staff ML Systems Engineer to architect and build the distributed infrastructure powering large-scale machine learning workflows across the organization.

This role sits at the intersection of ML, distributed systems, and platform engineering. You will design scalable systems for data processing, model training, evaluation, and post-processing while enabling teams to develop and operate production-grade workflows.

Qualifications

• 5+ years of experience building distributed systems, backend infrastructure, ML platforms, or large-scale data processing.
• Strong Python programming with concurrency and performance optimization.
• Experience with distributed computing frameworks such as Ray, Spark, Dask, or similar.
• Experience designing and scaling data pipelines or ML workflows.
• Ability to work cross-functionally and drive decisions across teams.

Responsibilities

• Design and build scalable distributed ML pipelines across data processing, model training, evaluation, and post-processing workflows.
• Architect distributed execution systems with scheduling, resource allocation, and fault tolerance.
• Develop reusable abstractions, frameworks, and libraries to simplify pipeline development.
• Optimize performance across CPU/GPU environments to improve throughput and reliability.
• Partner with ML engineers, data engineers, and infra teams to productionize workflows.

Skills

Distributed systems

Python programming

Concurrency & performance

ML workflows

Tools

Ray

Spark

Dask

Kubernetes

DeepSpeed

Job description

FieldAI in Irvine is seeking a Staff ML Systems Engineer to architect and build the distributed infrastructure powering large-scale machine learning workflows across the organization.

This role sits at the intersection of ML, distributed systems, and platform engineering. You will design scalable systems for data processing, model training, evaluation, and post-processing while enabling teams to develop and operate production-grade workflows.