Job Description
We are pioneering the next generation of autonomous systems and are looking for a visionary 2026 Advanced Robotics & AI Integration Engineer to join our elite engineering team in San Francisco. As we approach the 2026 technological horizon, we are building the infrastructure for next-level human-machine collaboration.
In this pivotal role, you will lead the integration of cutting-edge artificial intelligence models with complex robotic hardware, ensuring seamless operation in dynamic environments. You will work at the intersection of hardware constraints and software scalability, pushing the boundaries of what is possible in autonomous navigation and decision-making.
Why Join Us?
- Work on high-impact projects that define the future of automation.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a hub in the heart of San Francisco.
Responsibilities
- Architect and implement robust software pipelines for integrating deep learning models into real-time robotic control systems.
- Optimize algorithms for edge computing environments, ensuring low-latency response times under hardware constraints.
- Collaborate cross-functionally with mechanical engineers to refine sensor fusion and actuator control strategies.
- Debug and resolve complex system-level issues involving hardware-software integration and firmware communication.
- Lead code reviews and mentor junior engineers in best practices for robotics and AI deployment.
- Stay abreast of the latest advancements in neural networks and robotics to continuously improve system performance.
Qualifications
- Master’s degree or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related field.
- Minimum of 5 years of professional experience in robotics software development or AI integration.
- Proficiency in programming languages such as Python, C++, and ROS (Robot Operating System).
- Strong understanding of machine learning frameworks (TensorFlow, PyTorch) applied to physical systems.
- Experience with embedded systems, Linux, and version control (Git).
- Demonstrated ability to troubleshoot complex hardware-software integration challenges.