FieldAI · 4 months ago
1.61 ML Infrastructure Engineer — ML Platform, Tooling & Systems
Irvine, CA
Full-time
Hybrid
Mid Level
$70K/yr - $300K/yr
3+ years expField AI is transforming how robots interact with the real world by building reliable AI systems for complex challenges in robotics. They are seeking an ML Infrastructure Engineer to develop the software platform and tooling that supports fast AI development and deployment across their ML and robotics stacks.
Enterprise SoftwareRoboticsRobotic Process Automation (RPA)
Responsibilities
Build ML Infrastructure & Developer Tooling
Design and implement internal tools, libraries, and CLI utilities that streamline experimentation, model training, and evaluation
Improve local and cloud development environments using Docker, internal package registries, and monorepos
Build reusable templates and interfaces for training, evaluation, and inference pipelines
Support the ML Lifecycle (Data → Models → Deployment)
Develop pipelines for dataset ingestion, transformation, versioning, and validation
Automate model training, evaluation, packaging, and deployment to cloud and edge environments
Ensure integrity and traceability across data, code, and model artifacts
Improve Build Systems and Developer Experience
Maintain and evolve a shared monorepo across ML, robotics, and software teams
Leverage Bazel or similar systems to enable fast, reproducible builds and tests
Enhance developer workflows to support consistent environments and reduce friction
Own CI/CD and Automation for ML Systems
Build and maintain CI/CD pipelines (e.g., GitHub Actions, AWS Step Functions) for ML experimentation and deployment
Automate regression testing and benchmarking models
Develop observability tools: dashboards, telemetry systems, and model health monitoring
Collaborate Across Engineering & Research Teams
Work closely with ML scientists, software engineers, and roboticists to translate high-level platform needs into robust engineering solutions
Participate in code and design reviews, documentation, and cross-team planning
Qualification
Required
3+ years of industry experience in software engineering, infrastructure, MLOps, or DevOps roles
Deep familiarity with the ML lifecycle, including data preparation, model training, packaging, and deployment
Strong software engineering foundations: proficiency with Git, Python, and system design
Experience building and managing containerized environments (e.g., Docker) and working with orchestration tools (e.g., Kubernetes)
Hands-on experience with CI/CD workflows and infrastructure-as-code (e.g., Terraform, AWS CDK)
Experience with cloud ML platforms (AWS, GCP, or Azure)
A strong product mindset — building internal tools with empathy for researchers and engineers
Preferred
Experience with distributed training frameworks (e.g., PyTorch DDP, FSDP, DeepSpeed, Megatron)
Familiarity with orchestrating large-scale training jobs using Kubernetes-based platforms (e.g., Ray, SageMaker, EKS, Karpenter)
Background in hybrid edge-cloud ML deployments or infrastructure supporting robotic systems
Prior work in environments requiring real-time ML performance, safety validation, or regulatory traceability
Company
FieldAI
FieldAI is the general-purpose brain making robots autonomous in complex, risky, real-world environments.
51-200 employees
H1B Sponsorship
FieldAI has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2026 (6)
2025 (9)
Funding
Current Stage
Growth StageTotal Funding
$405MKey Investors
Hyundai Motor GroupBezos Expeditions,Prysm Capital,Temasek Holdings
2026-02-22Corporate Round
2025-08-20Series Unknown· $91M
2025-08-20Series A· $314M
Leadership Team
Ali Agha
Founder and CEO
Recent News
Crunchbase News
2025-12-19
Company data provided by crunchbase