Software Engineer, Computer Vision / Machine Learning
About this role
Designing and implementing image processing algorithms and models for ground and flight products forms the core daily routine for this role, with a strong emphasis on low latency and deployability. Team members build out image data products while establishing the foundational machine learning data engineering architecture to support a growing pipeline of computer vision workloads. Engineers collaborate closely with mission and payload teams to handle model handoffs, manage verification and validation testing, and optimize systems for both cloud environments and edge deployment.
Muon Space expands its high performance compute team to accelerate mission-critical data products across satellite constellations. Ideal candidates bring solid experience in shipping production-grade image computation systems, paired with strong Python and PyTorch competencies. Professionals who thrive in cross-functional environments and enjoy tackling complex aerospace challenges will find a fitting home within this Silicon Valley team.
What you will do
- Design, train, evaluate, and iterate on image processing models for ground processing and onboard flight systems.
- Build and own the image and machine learning data engineering foundation.
- Optimize algorithms and models for low-latency operation on cloud compute environments and edge or onboard deployment in constrained environments.
- Contribute to high-performance reference algorithms and implementations while benchmarking them effectively.
- Transition algorithms into the cloud serving stack and partner with payload teams to define requirements.
- Manage verification and validation processes including unit, integration, and performance regression tests.
What you need
- Hold a Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Applied Math, or a related technical field.
- Bring at least three years of professional experience developing, shipping, and operating image computation or machine learning systems.
- Demonstrate strong PyTorch skills spanning model design, training, and end-to-end evaluation.
- Possess production experience with low-latency image computation models deployed as containerized workloads on cloud infrastructure such as AWS.
- Show hands-on machine learning data engineering expertise including dataset curation, labeling, and versioning.
- Write tested, packaged, and code-reviewed Python code that runs unattended in production environments.
- Maintain the ability and willingness to obtain and maintain a U.S. security clearance.
Nice to have
- Geospatial or remote-sensing imagery experience with optical, IR, or SAR
- Active-learning, data-centric machine learning, or labeling workflows
- Deploying computer vision or image processing models to edge or embedded targets
- GPU acceleration utilizing CUDA, HIP, or similar technologies
- CI/CD for containerized workloads including performance regression testing
Benefits
- Competitive equity grant
- Medical, dental, and vision insurance
- 401k retirement plan
- Short and long term disability and life insurance
- Three weeks paid vacation for new employees along with 12 paid holidays
- Unlimited sick time and paid parental leave
Skills and tech stack
Questions candidates ask
What is the remote work policy for this role?
This position is hybrid and requires working on-site in the San Jose, California office three days per week. The company is currently registered and able to hire in a specific list of U.S. states.
What is the salary range for this position?
The salary range for this role is $212,000 to $233,000. Final compensation is determined based on skills, qualifications, experience, and geographic location during the interview process.
What technical stack and tools will I use?
You will use strong Python and PyTorch skills to design, train, and evaluate models end-to-end. The work involves deploying containerized workloads on cloud infrastructure such as AWS.
Are there clearance requirements for applicants?
This role requires the ability and willingness to obtain and maintain a U.S. security clearance, though an active clearance is considered a plus. Applicants must also conform to U.S. Government export control regulations.