Build and maintain data pipelines and core robotics software for perception, spatial reasoning, teleoperation, simulation, and deployment. Support ML training datasets, write high-performance systems code (C/C++/Rust), improve simulation workflows, and collaborate across robotics, ML, and hardware teams to deliver reliable, production-ready autonomous systems.
Company Description
Role Description
What You’ll Do
Qualifications
Bonus Points
Why Join Us
Autonomique is at the forefront of innovation in Physical AI, addressing key challenges in autonomy such as perception, spatial reasoning, and dexterity. Our robotics intelligence framework delivers reliable, autonomous solutions for industries with complex operational demands. With advanced bi-manual robots, we are enabling groundbreaking advancements in manufacturing by empowering robots to perform critical real-world tasks. We are driven by the mission to make autonomous systems practical and impactful today.
This is a high-impact, high-ownership role for a builder who wants to improve the software foundation behind our robots. You will work directly with the founding team to strengthen the systems that power perception, spatial reasoning, teleoperation, training, deployment, and internal infrastructure. This role involves contributing to systems that enable robots to interpret and reason about their environment. We are looking for someone who values equity participation and wants to capture the upside of the value they create. You won't just be an employee; you will be a key architect of our success. Strong systems roles in robotics and simulation are common across the space, but we place particular emphasis on building reliable, production-ready systems that integrate perception, learning, and real-world deployment.
- Build Data Infrastructure: Design and maintain the pipelines that collect, store, organize, and version robot data from teleop, sensors, and deployments.
- Support AI Training: Help turn raw robot data into clean, usable datasets for model training and evaluation.
- Contribute to Perception and Reasoning Systems: Help build systems that enable robots to interpret their environment and structure information for downstream decision making.
- Strengthen Core Robotics Software: Contribute to the software infrastructure that underpins robot behavior, debugging, testing, and deployment.
- Ship Efficient Code: Write high-performance C, C++, or Rust code for systems where latency, reliability, and efficiency matter.
- Work Across the Stack: Collaborate with robotics, ML, and hardware engineers to make the full development loop faster and more reliable.
- Improve Simulation Workflows: Help connect simulation environments to real robot workflows for testing, iteration, and validation.
- Education: BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, or a related field.
- Experience: 3+ years building software for robotics, embedded systems, simulation, or other performance-critical environments.
- Systems Programming: Expert-level programming in C, C++, or Rust, with strong Python skills.
- Robotics Exposure: Experience with robots, teleoperation, or robotics middleware is strongly preferred.
- Simulation Experience: Familiarity with at least one simulation environment such as MuJoCo, Isaac Sim, Gazebo, or similar.
- Machine Learning: Experience training, fine-tuning, or evaluating models in computer vision, language, or multimodal domains. Comfortable working with datasets, model iteration, and evaluation workflows.
- Engineering Excellence: Strong debugging, profiling, and software design skills, with a track record of shipping reliable systems.
- Startup Mindset: Comfortable working in a fast-moving environment where priorities evolve and ownership is high.
- Experience with ROS or ROS2.
- Familiarity with data pipelines, storage systems, or experiment tracking.
- Familiarity with modern computer vision approaches.
- Experience with real-time systems, networking, or distributed systems.
- Exposure to ML training workflows, dataset management, or robot learning.
- Open source contributions or a portfolio of systems-level work.
- Ownership: We offer a substantial equity package designed for those who believe in our mission and want to be rewarded for the company's long-term success.
- Impact: Work directly on real-world projects and see your code deployed in the real world immediately. We are already shipping robots in production.
- Culture: A collaborative, high-velocity supportive environment conducive to both personal and professional growth.
Similar Jobs
Artificial Intelligence • Robotics • Automation • Manufacturing
Build and maintain data pipelines and core robotics software to support teleoperation, training, deployment, and simulation. Write high-performance systems code (C/C++/Rust), prepare datasets for ML training, improve simulation workflows, and collaborate cross-functionally to increase reliability, performance, and automation of deployed robots.
Top Skills:
CC++Data PipelinesDistributed SystemsExperiment TrackingGazeboIsaac SimMujocoNetworkingPythonReal-Time SystemsRobotics MiddlewareRosRos2RustStorage SystemsTeleoperation
Angel or VC Firm • Financial Services
Design and build machine-learning-driven robotic systems that operate in the real world, support portfolio company growth, influence product and technical direction, and advance company and career outcomes.
3 Hours Ago
AdTech • Cloud • Digital Media • Information Technology • News + Entertainment • App development
Implement and deploy deep-learning, computer vision, and procedural modeling algorithms (primarily in Python). Apply state-of-the-art ML and graphics research to convert large 2D/3D geospatial datasets into high-fidelity 3D content. Collaborate with founders on product vision, manage code with Git, and deploy/test at scale using Unix-based systems.
Top Skills:
C++GitPythonUnix Shell
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine


.png)