Research Scientist, Vision-Language-Action Models

Matter Inc • Menlo Park, CA

20h

About The Position

Matter is building the AI-native autonomy stack for physical manufacturing in
the United States. We operate as a contract manufacturer, deploying software and
autonomy in our own factories, which gives us something most AI companies don’t
have: a live production environment as a training ground. Our long-term vision
is to become the infrastructure layer for American manufacturing, the way AWS
became infrastructure for software.

We are hiring a Research Scientist to lead the development and deployment of
Vision-Language-Action (VLA) models for robotic manipulation in live
manufacturing work cells. This is not a lab role. You will train models, close
the Sim2Real loop, and deploy them on physical robots running production
programs.

Matter’s Sim2Real pipeline spans NVIDIA Isaac Sim, physics-accurate virtual
builds of our modular assembly equipment, and 100% data collection from real
factory operations. You will operate at the center of this flywheel design,
improving models with every production run.

WHY MATTER

Most VLA research is validated in a lab or on a tabletop. At Matter, your models
run on a production factory floor, handling real parts for real customers. The
feedback loop is immediate and grounded. The training data is yours because the
factory is yours. No one else in this space has that combination at the stage
we’re at.

Requirements

• PhD, Graduate or equivalent research depth in robotics, machine learning, or a related field
• Hands-on experience training and deploying VLA, VLM, or generalist robot policies on physical hardware (not just simulation)
• Strong foundation in imitation learning, reinforcement learning, and general machine learning methods
• Proficiency in PyTorch; experience with NVIDIA Isaac Sim, MuJoCo, or similar physics engines
• Ability to debug the full stack: model architecture, training data quality, sim calibration, sensor noise, and hardware edge cases
• Comfort operating in a high-velocity, ambiguous environment where you own systems end-to-end

Nice To Haves

• Experience with MARL or multi-robot coordination
• Background in manufacturing, industrial automation, or robotic assembly

Responsibilities

• Develop and fine-tune VLA models for precision assembly tasks, including dexterous manipulation, part handling, and test operations
• Design and manage the Sim2Real training pipeline: domain randomization, synthetic data generation, physics simulation (NVIDIA Isaac Sim, MuJoCo), and sim-to-physical transfer
• Build evaluation frameworks to benchmark real-world manipulation performance against manufacturing tolerances and repeatability requirements
• Collaborate with controls and automation engineers to fuse learned policies with traditional control architectures for production safety
• Contribute to the Physical AI architecture decisions: model selection, data strategy, training infrastructure, and deployment protocols
• Publish novel research in top tier 1 conferences — though shipping production systems is the primary measure of success

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree