GrayMatter Robotics

Senior Applied AI Engineer

Los Angeles - HQ · Senior

Sponsorship not specifiedDetected 174 days ago

PythonC++Machine LearningDeep LearningLLMsProcess ImprovementRoboticsMechanical DesignResearch

About the role

Our robots take on the tedious, hazardous, and ergonomically demanding work that has kept manufacturing dependent on a shrinking skilled workforce, delivering superhuman performance.
Our systems are in active production today, adapting autonomously to real geometries, real materials, and real process variation without reprogramming.
We hire people who want to solve hard physical problems at an industrial scale.

Design, implement, and train state-of-the-art AI models for perception, inspection, decision-making, and control in real-world robotic manufacturing systems.
Own and advance synthetic data generation pipelines, leveraging generative AI techniques for complex 3D geometry and environment, physics-based simulation, and image data, and scaling them across diverse processes and applications.
Optimize, deploy, and maintain ML models on production robotic systems, considering latency, reliability, and hardware constraints.
GrayMatter Robotics is a well-capitalized Physical AI company headquartered in Los Angeles, building Factory SuperIntelligence (FSI) through systems that learn, adapt, and develop genuine process intelligence across every part they touch.
We deliver our system through a Robots-as-a-Service (RaaS) model that converts capital expenditure into an operating subscription, making Physical AI accessible to the manufacturers who need it most.

Strong proficiency in Python is required
Proven ability to diagnose and solve ambiguous, system-level problems and iterate quickly under real-world constraints.

Deep understanding and hands-on experience using physics engines and robotics simulation platforms (e.g., Isaac Lab, MuJoCo) to solve complex real-world robotics problems.
Hands-on experience with 3D data (point clouds, meshes, SDFs, CAD-derived geometry) and related tooling.
Experience with robotics middleware and tooling (e.g., ROS/ROS 2) and deployment on real robotic hardware.
Prior experience working in industrial, manufacturing, or high-mix automation environments.
A publication track record, or demonstrated interest in publishing applied research in venues such as ICRA, CoRL, RSS, IROS, RA-L, or T-RO, balanced with a strong bias toward real-world production impact.
PLEASE NOTE: This is a Q3/Q4 2026 hire.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
We celebrate diversity and are committed to creating an inclusive environment for all employees.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

Develop and deploy multi-modal inspection and health monitoring systems, integrating vision, 3D sensing, force/torque, and other sensor modalities.

AI team at GrayMatter Robotics, a cross-functional group responsible for designing, building, and operationalizing AI capabilities across GMR's products and customer deployments.
The team serves as a horizontal AI function, working across simulation, data, perception, inspection, learning-based control, process optimization, and system validation to enable robust autonomy for GMR's robots and factories in high-mix manufacturing environments.
The team operates end-to-end from problem formulation and data strategy to model development, simulation, deployment, and long-term performance monitoring collaborating closely with robotics software, solutions engineering, applications, process engineering, hardware, and deployment teams.
The team's mandate is to ensure that AI systems scale across processes, customers, and sites, and perform reliably on real robots in real factories, today, not just in controlled demonstrations.
This role values strong technical depth and sound research judgment, but places a clear priority on system ownership, execution, and measurable business impact.
Publishing and external technical contributions are encouraged when they naturally emerge from deployed systems while meaningfully advancing both GMR's products and the broader robotics community; however, successful delivery, robustness, and customer-visible outcomes are the primary measures of success.

This listing is sourced directly from GrayMatter Robotics's careers page and normalized into a canonical job model.