Senior Robotics​/Autonomy Engineer – AI Sensor & Edge Systems

Senior Robotics / Autonomy Engineer – AI Sensor & Edge Systems

Duration: 6+ Months (Contract)

Location:

San Francisco, CA Onsite required (No remote option) - Need only locals

In-Person Technical Interview (San Francisco)

3 openings

Focus on below :

• Background / Companies:
  Tesla (Autopilot, Dojo, Data Engine), Uber ATG/Aurora, Cruise, Waymo deployment teams (non-research), Zoox, Nuro, robotics startups, defense robotics, and industrial, agriculture, mining, or construction autonomy companies
• Core Profile:
  Hands-on autonomy builders who design, deploy, and iterate on real systems rather than research-only work
• Key Resume Signals:
  Built and deployed perception systems on real vehicles or machines; experience with data engines and fleet-scale data pipelines (not just model training); edge inference on real hardware
• Hardware & Stack Indicators: NVIDIA Jetson Orin/Xavier, ROS/ROS2, CAN bus, LiDAR, cameras, and multi-sensor integration
• Deployment
  
  Experience:
  
  Onsite testing, field deployments, hardware bring-up, debugging in real-world conditions, and “built from scratch” language
• Strong
• Typical Titles:
  Autonomy Engineer, Perception Engineer, Robotics Software Engineer, Senior/Staff Autonomy Engineer, Robotics Engineer, Embedded AI Engineer, Edge AI Engineer

Role Overview

We are building next-generation sensor and edge-compute systems that enable heavy machinery to see, understand, and learn from the real world. This role is for a high-velocity implementer, not a researcher.

You will design, build, deploy, and iterate on real-world AI systems mounted on large machines operating in harsh environments. If you thrive under tight timelines, imperfect data, brutal bandwidth constraints, and hands-on hardware integration, this role is for you.

This initiative is part of a broader vision to collect large-scale machine data for reinforcement learning, imitation learning, and foundation model development, similar to how Tesla approaches autonomy.

Key Responsibilities

• Design and deploy modular sensor stacks (LiDAR, cameras, CAN bus, edge compute) across multiple machine types
• Build low-latency AI pipelines under constrained bandwidth and compute environments
• Integrate edge AI systems with heavy machinery and autonomous platforms
• Enable efficient data capture, filtering, and offloading via 5G / Wi-Fi
• Identify critical data signals required for model training and continuously refine data pipelines
• Rapidly iterate on AI workflows to support reinforcement learning and imitation learning
• Work onsite to mount, test, debug, and harden systems in real-world conditions
• Deliver large amounts of functional output under aggressive timelines

Required Technical Skills

• Strong hands-on experience in AI development for Robotics / Autonomy
• Proficient in C++ and/or Python
• Experience building sensor stacks including:
• LiDAR
• Cameras
• CAN BUS
• Edge compute systems
• Prior work with:
• Autonomous vehicles
• Robotics platforms
• UAV sensing systems
• DIY robots that operate in real environments
• Comfortable working with imperfect data, hardware constraints, and field deployments

Preferred Skills

• Experience with transformer-based models and AI agents
• Familiarity using multiple AI agents simultaneously
• Exposure to reinforcement learning, imitation learning, or world models
• Background in edge AI optimization and bandwidth-constrained systems
• Previous experience at Uber, Tesla, or similar autonomy-driven companies

Soft Skills & Mindset

• Self-starter / go-getter mentality
• Extremely autonomous and execution-focused
• Thrives in fast-paced, ambiguous environments
• Comfortable cutting corners when needed to deliver results
• Strong problem-solving instincts with a “make it work” attitude
• Energized by shipping in weeks, not publishing in months

Why This Role

• Direct impact on real machines in the field
• Opportunity to shape large-scale AI data collection for foundation models
• Work alongside senior architects tackling complex autonomy challenges
• High ownership, high trust, and rapid execution