Machine Learning Engineer

About the role

About Andromeda

Andromeda is building autonomous surgical robots designed to help surgeons perform procedures more safely, consistently, and efficiently. Our engineers work across robotics, software, hardware, machine learning, and clinical operations to bring robotic systems from concept to real-world deployment. We are a small, highly collaborative team that values ownership, curiosity, technical rigor, and the ability to move quickly from idea to execution.

The Role

We are looking for a Machine Learning Engineer to work across the full stack of our surgical robotic platform: the robotics system, the ML platform, and the infrastructure that powers model training. You will build machine learning models to solve problems specific to surgical robotics, many of which do not have existing research or pre-trained solutions to start from.

What You'll Do

- Train and build machine learning models for real-world robotic applications.

- Work across the robotics stack, the ML platform, and the infrastructure for model training.

- Build models from scratch for novel problems where prior research or pre-trained models do not apply.

- Write clean, testable, production-quality code that integrates with the broader system.

- Collaborate closely with robotics, software, and clinical teams to bring new capabilities to the robot.

What We're Looking For

Machine Learning

- Hands-on experience training machine learning models, either in graduate studies or professional work. This is a must, not something to learn on the job.

- Ability to build models from scratch for problems where existing research does not apply, rather than only fine-tuning or retraining existing models.

- Ability to scope out an ambiguous ML problem and define an approach when there is no established path to follow.

Software Engineering

- Ability to write clean, maintainable, production-quality code.

- Experience writing tests and validating software behavior. Testing is a core part of how we build, not an afterthought.

- Comfortable working across multiple parts of the technical stack, from robotics to ML platform to training infrastructure.

- Strong debugging and problem-solving skills.

Ownership & Startup Mindset

- Strong ownership mindset and ability to independently drive projects forward.

- Comfortable operating in a fast-moving environment with evolving priorities.

- The project needs to be delivered, and you do what it takes to get it there.

- Willingness to seek feedback, iterate quickly, and collaborate closely with teammates.

Nice to have

- Experience with computer vision or vision models.

- Experience deploying high-performance ML models in production (for example, converting trained models to ONNX or similar formats for C++ inference).