Job description

FieldAI ’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. What You’ll Get To Do Design and manage scalable ML infrastructure with IaC tools (Terraform, CloudFormation). Develop and optimize cloud-based pipelines for training, evaluation, and inference on multimodal datasets. Build and operate data systems for large-scale video ingestion, indexing, and storage. Maintain MLOps workflows for versioning, experiment tracking, reproducibility, and CI/CD. Ensure reliability and observability with monitoring, logging, and alerting. Collaborate with AI/ML Engineers to productionize workflows. Optimize infrastructure for performance and cost across cloud and edge. Enforce best practices in security, compliance, and maintainability. Mentor and manage junior engineers, providing technical guidance and career development. What You Have 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 a strong foundation in software engineering best practices. Proven experience with distributed systems, cloud platforms (AWS preferred), containerization and orchestration (Docker, Kubernetes/EKS, Ray), and serverless. Hands-on experience building ML pipelines for distributed training and large-scale inference. Strong knowledge of data management at scale, including preprocessing and retrieval of video/image datasets. Proficiency with CI/CD pipelines, infrastructure-as-code (Terraform, CloudFormation), and automation. Familiarity with MLOps tools (MLflow, Kubeflow, Airflow). Experience with system monitoring and observability in production. The Extras That Set You Apart Experience with vector databases (OpenSearch, Pinecone, Weaviate) for indexing and retrieval. Familiarity with distributed training frameworks (Horovod, DDP/FSDP, DeepSpeed, Ray). Hands-on experience with GPU orchestration and auto-scaling (Karpenter, SageMaker, EKS). Experience with agentic AI deployment workflows, orchestration frameworks, and retrieval-augmented generation. Strong knowledge of security and compliance in ML and cloud environments. Our salary range is generous and we consider each individual’s background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market. Why Join FieldAI in Irvine? In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics’ hardest challenges: reliable deployment outside the lab. Our Field Foundational Models™ raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use. You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments. Be Part of the Next Robotics Revolution We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world. Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field-ready autonomy looks like. We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected status.

Requirements

Must-haves

What You’ll Get To Do
Design and manage scalable ML infrastructure with IaC tools (Terraform, CloudFormation).
Develop and optimize cloud-based pipelines for training, evaluation, and inference on multimodal datasets.
Build and operate data systems for large-scale video ingestion, indexing, and storage.
Maintain MLOps workflows for versioning, experiment tracking, reproducibility, and CI/CD.
Ensure reliability and observability with monitoring, logging, and alerting.
Collaborate with AI/ML Engineers to productionize workflows.
Optimize infrastructure for performance and cost across cloud and edge.
Enforce best practices in security, compliance, and maintainability.
Mentor and manage junior engineers, providing technical guidance and career development.
What You Have
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 a strong foundation in software engineering best practices.
Hands-on experience building ML pipelines for distributed training and large-scale inference.
Strong knowledge of data management at scale, including preprocessing and retrieval of video/image datasets.
Proficiency with CI/CD pipelines, infrastructure-as-code (Terraform, CloudFormation), and automation.
Familiarity with MLOps tools (MLflow, Kubeflow, Airflow).
Experience with system monitoring and observability in production.
The Extras That Set You Apart
Experience with vector databases (OpenSearch, Pinecone, Weaviate) for indexing and retrieval.
Familiarity with distributed training frameworks (Horovod, DDP/FSDP, DeepSpeed, Ray).
Hands-on experience with GPU orchestration and auto-scaling (Karpenter, SageMaker, EKS).

Nice-to-haves

Proven experience with distributed systems, cloud platforms (AWS preferred), containerization and orchestration (Docker, Kubernetes/EKS, Ray), and serverless.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigomlci/cdpythontypescriptawsdockerkubernetes

Platform: lever
Effort: quick