Description
1.55 AI Research Engineer, Foundation Models & Robot Learning
Team: Research
Location: Pittsburgh, PA
Commitment: Full time
Workplace Type: onsite
FieldAI is transforming how robots interact with the real world. We build risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence. We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment. Our solutions are already deployed globally, and we continuously improve model performance through rapid iteration driven by real field use.
In Pittsburgh, we’re pushing the frontier of embodied intelligence by designing robot learning systems that scale across tasks, environments, and robot embodiments. We work on robotics foundation models, from vision and language to control, and we deploy what we build on real robots solving real problems in unstructured, real-world settings.
We are looking for a Robotics Research Engineer to build intelligent robotic systems that operate robustly in complex, unstructured real-world environments. This role sits at the intersection of robotics systems engineering and modern AI/ML, with a strong emphasis on deploying learning-enabled autonomy on real robots.
You will work across perception, planning, control, and hardware–software integration, while also developing and integrating machine-learning models (e.g., large-scale perception models, robot learning policies, multimodal and language-conditioned systems) as core components of deployed robotic systems.
Success in this role is defined by the ability to connect learning algorithms to physical robots, reason through real-world constraints, and iterate from research ideas to working fielded systems.
What You’ll Get To Do
- Design and implement robotics software systems for perception, state estimation, planning, and control using ROS2-based stacks.
- Develop, integrate, and evaluate machine-learning models for robotics, including perception models, learned policies, multimodal or language-conditioned components, and robot learning systems.
- Work with large research and production codebases, adapting research code, fixing logic and configuration issues, and debugging system-level failures.
- Train, fine-tune, or adapt ML models and integrate them into real-time robotics pipelines.
- Bring up, configure, and operate physical robotic platforms and sensors, supporting lab and field experiments.
- Design systems that handle real-world complexity, including noisy sensors, limited compute, real-time constraints, and dynamic environments.
- Collaborate across research, software, and hardware teams to rapidly iterate on end-to-end robotic capabilities.
- Clearly communicate technical approaches, assumptions, tradeoffs, and debugging strategies.
What You Have
- Strong candidates will demonstrate depth in robotics systems and practical experience applying AI/ML to embodied platforms.
- Hands-on experience with robotics frameworks and tools (e.g., ROS2, C++, Python, OpenCV, Eigen, GTSAM).
- Experience modifying and extending robotics or research codebases, including ML-enabled systems.
- Practical experience working with physical robots and sensors (mobile robots, manipulators, perception sensors, inertial sensors, etc.).
- Experience integrating machine-learning models into robotics pipelines, such as perception, navigation, manipulation, or policy learning.
- Understanding of real-world robotics constraints, including latency, hardware limitations, failure modes, and deployment challenges.
- Ability to communicate clearly while reasoning through system design and debugging.
The Extras That Set You Apart
- Experience developing or deploying advanced ML systems for robotics, including fine-tuning VLMs/LLMs, multimodal embodied models, or large-scale perception systems.
- Experience with professional robotic platforms and sensors.
- Experience with hardware prototyping and rapid iteration, including sensor integration and hardware–software co-design.
- Publications in robotics or machine learning venues.
Why Join FieldAI?
FieldAI is tackling one of robotics’ hardest problems: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ advance perception, planning, localization, and manipulation with an emphasis on explainability and safety, so our systems can be trusted where it matters most.
You will work alongside a world-class team that values creativity, resilience, and bold thinking. We bring a decade-long track record of real-world deployments, strong performance in DARPA challenges, and experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX.
Our Pittsburgh team is growing and focused on robot learning and embodied intelligence, building and deploying learning systems that generalize across tasks and robot embodiments. You will work on research that connects foundation models, large-scale training, and real-world robotic performance, with a clear path from ideas to field capability.
Be Part of the Next Robotics Revolution
Solving problems at this scale takes a team as unique as the mission. We are looking for people who push beyond conventional approaches, enjoy tackling tough and ambiguous questions, and bring interdisciplinary perspective. Our success depends on exceptional AI researchers and engineers, as well as strong software developers, product designers, field deployment experts, and communicators who can turn breakthroughs into real capability.
We are headquartered in Mission Viejo (Irvine adjacent), Southern California, with teammates across the US and around the world. Join us to shape the future of embodied intelligence as part of a fun, close-knit team building systems that work in the real world.
Equal Opportunity
FieldAI celebrates diversity and is committed to creating an inclusive environment for all employees. Candidates and employees are evaluated based on merit, qualifications, and performance. We do not discriminate on the basis of race, color, religion, sex, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected status.
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