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# Machine Learning Engineer

- **Company:** Andromeda Surgical, Inc.
- **Location:** South San Francisco, CA, United States
- **Salary:** $150,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Computer Vision, C++ (Programming Language), Machine Learning, Azure Machine Learning, Software Engineering, ONNX (Open Neural Network Exchange) Format, Production Code
- **Published:** September 16, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=200f64d7377fc1ac

## About the Role

* 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).
 * Experience with C++.
 * Experience with robotics or hardware-adjacent systems.
 * Experience working in startup environments.

## Description

* 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.