About the job
FOUNDING ROBOTICS RESEARCHER
JOB TITLE: Founding Robotics Researcher
LOCATION: Onsite (Bay Area, CA)
COMMITMENT: Full-time / Founding Team
COMPENSATION: Competitive Salary + Meaningful Equity, Pay Frequency: Monthly
HIGHLIGHT: Support Immediate H1 Visa Application
ABOUT DEEPREACH AI
DeepReach AI is at the forefront of creating the foundational infrastructure for real-world embodied artificial intelligence. We prioritize large-scale teleoperation data, Vision-Language-Action (VLA) training, and authentic deployment environments, steering clear of mere staged demonstrations. Our focus is on real distributions, effective deployments in real-world settings, and rapid iteration to bridge the gap between model training and physical functionality.
THE ROLE
As the Founding Robotics Researcher, you will lead the VLA and policy learning initiatives. Your responsibilities will extend beyond data consumption; you will establish the data strategy, deploy models on actual robots, and design experiments aimed at enhancing deployment performance. This is an ideal opportunity for individuals eager to build a research engine within a startup, comfortable transitioning between PyTorch and hardware debugging as necessary.
KEY RESPONSIBILITIES
- VLA & Policy Training: Architect and train VLA models for real-world tasks and develop fine-tuning pipelines utilizing deployment-collected data.
- Data System Design: Create teleoperation data collection frameworks and construct filtering, curation, and scaling pipelines to tackle distribution gaps.
- Hardware Integration: Deploy policies to physical robot arms and sensor stacks, optimizing for latency, calibration, and system reliability.
- Research–Deployment Loop: Establish internal benchmarks aligned with actual tasks and transform model failures into actionable data and system enhancements.
- Systems Debugging: Engage in hands-on work with robotic arms, grippers, and multi-camera systems to debug perception, policy, and control loops.
- Experimental Leadership: Design and define critical experiments and develop evaluation metrics linked to physical success rates.

