Robotics Machine Learning Engineer

As a Machine Learning Engineer at Plus One Robotics, you will develop and maintain the code and infrastructure responsible for collecting data from, training and deploying models to, and evaluating the behavior of our production warehouse pick and place robotics systems. Our installations perform over 1.5 million picks a day, ensuring a continuous stream of edge cases and distributional shift that are immediately handled by our human‑in‑the‑loop system and must be incorporated into new autonomous models.

We borrow heavily from open source and academic research communities and you will be responsible for adapting these cutting‑edge techniques to our demanding industrial setting. Together with a team of architects, data scientists, theoreticians, and robot programmers, you will implement scalable, robust systems that serve our clients.

• Read, understand, and utilize 3rd‑party documentation of code (repos) and theoretical advances (papers).
• Build systems for functionality, scalability, and maintenance.
• Adapt machine learning algorithms and libraries (Deep Neural Nets, Reinforcement Learning, Imitation Learning) for our applications.

• 3 years experience or Masters + 1 year
• Skilled in Python, with familiarity with PyTorch, Hugging Face, LeRobot or similar libraries.
• Familiarity with cloud computing infrastructure such as GCP or AWS
• Excellent analytical and communication skills

• 5+ years experience
• Previous work with industrial robots

Full‑time, 40 hours per week, Monday‑Friday, 9:00 am‑6:00 pm.

Must be able to travel both domestically within the US and internationally (including the EU, Canada, and Australia) without any travel restrictions. May travel up to 20% of the time during deployments.

Must be able to provide documentation that shows authorization to legally work in the U.S.

The salary for this role is dependent on experience. Depending on level of experience, this role starts at $110,000 per year and is a bonus‑eligible position.

Plus One Robotics offers a wide range of employee benefits for our full‑time positions including healthcare benefits, a flexible paid time‑off plan, professional development opportunities, and a paid maternity and paternity leave program.

This role will be located in either our San Antonio, TX headquarters or our Boulder, CO location. Applications will be accepted through the end of November 2025.