Senior Robotics / Autonomy Engineer

 Job Title: Senior Robotics / Autonomy Engineer – AI Sensor & Edge Systems

Experience : 15-20+ Years 

Duration: 6+ Months (Contract)

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

In-Person Technical Interview (San Francisco)

Visa Status: GC

Job Description:

·        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 Keywords: Fleet, vehicles, telemetry, logs, edge AI, sensor fusion, low-latency pipelines

·        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

·       Not research-oriented — this is about building and deploying