Senior Machine Learning Platform Engineer
Irvine, CA
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type Full time
Employment type in the employer’s listing: Full time
From the employer’s posting
What you’ll work on
Full postingDesign and manage scalable ML infrastructure using Terraform or CloudFormation
Develop and optimize cloud pipelines for training, evaluation, and inference
Build and operate data systems for large-scale video ingestion, indexing, and storage
Maintain MLOps workflows for versioning, experiment tracking, and CI/CD
From the employer’s posting
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.
Education & alternatives
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.
Tools in this posting
- Python
- TypeScript
- AWS
- Docker
- Kubernetes
- MLflow
- SageMaker
- Terraform
- Airflow
Source — Tool mentions in context
- 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.
- 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.
- 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.
- 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.
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.
- 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).
Posting record
Report an errorOpen 6 monthsWe first saw this listing 192 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Apr 15, 2026 · 192 days ago
- Recorded sightings
- 210
- Last seen by us
- Oct 24, 2026
- Employer says posted
- Sep 26, 2025
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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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.
Employment type
Full time
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Irvine, CA
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