Senior Machine Learning Engineer

FieldAI; Seattle (WA); On-site; USD 180,000 - 215,000; Full time

Job summary

FieldAI is looking for an experienced ML Engineer in Seattle, WA, to develop the next-generation Field Foundation Model (FFM) for autonomous robots. You will design and implement capabilities that enable deployment across various environments, collaborating with experts in robotics and software engineering.

This role involves working with cutting-edge technologies and solving complex challenges in reliable robot deployments while contributing significantly to the company’s mission. The position offers competitive compensation between $180,000 and $215,000 annually.

Qualifications

• 4+ years of industry experience in ML or Robotics.
• Deep understanding of deep learning architectures.
• Proven track record of deploying ML models.

Responsibilities

• Design, train, and deploy machine learning models.
• Architect and implement full-stack navigation solutions.
• Monitor models in production and automate retraining.

Skills

Proficiency in Python

Experience with ML frameworks (PyTorch, TensorFlow, JAX)

Knowledge of C++ for deployment

Education

Bachelor’s or Master’s degree in Computer Science, AI, Statistics, or related field

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.

As an ML Engineer at FieldAI, you will help build the next‑generation Field Foundation Model (FFM), powering a global fleet of autonomous robots deployed across diverse environments. Your contributions will directly shape how we scale – through advances in model architecture, training methodologies, and deployment strategies.

You’ll collaborate closely with machine learning scientists, software engineers, and robotics experts to design and implement FFM capabilities that generalize across tasks and environments. Beyond model development, you’ll also support deployment and monitoring to ensure smooth integration and reliable real‑world performance.

This role offers the opportunity to work with cutting‑edge technologies, solve complex challenges, and directly impact large‑scale robot deployments.

What You’ll Get To Do

Machine Learning modeling

• Design, train, and deploy state‑of‑the‑art machine learning models for end‑to‑end learning‑based navigation stack.
• Work with deep learning architectures such as transformers, convolutional networks to capture complex decision making.
• Architect and implement full‑stack end‑to‑end navigation solutions, covering perception, prediction, and planning.
• Explore novel data generation and collection pipelines to enrich training datasets.

Model Deployment, Monitoring & Performance

• Assist with deploying machine learning models into production environments.
• Continuously monitor models in production, detecting model drift, and automating retraining processes as applicable.
• Troubleshoot issues related to model deployment, performance, and system integration.

What You Have

Bachelor’s or Master’s degree in Computer Science, AI, Statistics, or a related field, with 4+ years of industry experience.

• Proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, or JAX, alongside working knowledge of C++ for deployment and system integration.
• Deep understanding of contemporary deep learning architectures, optimization, and evaluation, with a strong grasp of end‑to‑end navigation stack components — including perception, prediction, and path/motion planning.
• Proven track record deploying ML models into production environments, ideally within robotics, self‑driving, or NLP.

The Extras That Set You Apart

• Publications in top tier ML or robotics conferences

$180,000 - $215,000 a year

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 statu