Field AI
Senior Machine Learning Platform Engineer
Irvine, CA · On-site · Senior · Full-time · Posted Sep 26, 2025
- Experience
- 4+ years of industry experience in ML infrastructure or platform engineering.
- Education
- Bachelor’s/Master’s in Computer Science, Engineering, or related field (or equivalent experience).
About the job
Designs and operates scalable ML infrastructure and data pipelines that support training, evaluation, and inference for embodied AI systems deployed on cloud and edge hardware.
What you'll do
- Build and manage ML infrastructure, pipelines, and large-scale video data systems.
- Maintain MLOps, CI/CD, monitoring, and observability while optimizing reliability, performance, and cost.
- Collaborate with AI/ML engineers to productionize workflows and mentor junior engineers.
What they ask for
- Bachelor’s/Master’s in Computer Science, Engineering, or related field (or equivalent experience).
- 4+ years of industry experience in ML infrastructure or platform engineering.
- Strong coding skills in Python/TypeScript and experience with distributed systems, cloud platforms, containers/orchestration, and serverless.
- Hands-on experience building distributed-training and large-scale-inference ML pipelines; knowledge of large-scale image/video data management, CI/CD, IaC, MLOps, and production observability.
Nice to have
- Experience with vector databases, distributed training frameworks, or GPU orchestration and auto-scaling.
- Experience with agentic AI deployment, orchestration frameworks, retrieval-augmented generation, or ML/cloud security and compliance.
Tools
Python, TypeScript, AWS, Docker, Kubernetes/EKS, Ray, Terraform, CloudFormation
AI focus
Supports embodied AI by providing infrastructure and pipelines for multimodal training, evaluation, inference, and field deployment; preferred experience includes agentic AI and retrieval-augmented generation.
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