Low-Latency ML Image Engineer for Edge & Cloud

Muonspace; San Jose (CA); Hybrid; USD 212,000 - 233,000; Full time

Benefits offered by this job

Equity compensation

Medical dental vision insurance

401k retirement plan

Paid vacation + holidays

Parental leave

Job summary

Muon Space in San Jose, CA is expanding its HPC team to design and implement image processing algorithms powering ground and flight products. This role focuses on low-latency ML models, edge deployment, and data engineering foundations, with hybrid on-site work three days a week.

Work with mission and payload teams to advance cloud and edge compute for space missions, and contribute to production systems with robust verification and evaluation processes.

Qualifications

• Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Applied Math, or a related technical field.
• 3+ years of professional experience developing, shipping, and operating image computation or ML systems.
• Strong PyTorch skills, including designing, training, and evaluating models end-to-end.
• Production experience with low-latency image computation models deployed as containerized workloads on cloud infrastructure (AWS preferred).
• Hands-on ML data engineering: dataset curation, labeling, and versioning for training and evaluation.
• Strong Python skills beyond notebooks: tested, packaged, code-review code that runs unattended in production.
• Strong communication and ability to lead cross-functional technical discussions.
• Ability to obtain and maintain a U.S. security clearance; active clearance a plus.

Responsibilities

• Design, train, evaluate, and iterate on image processing models for Muon's ground processing and onboard flight systems.
• Build and own the image and ML data engineering foundation.
• Optimize algorithms and models for low latency operation on cloud compute environments, and edge/onboard deployment in constraint environments.
• Contribute to high-performance reference algorithms and implementations and benchmark them.
• Hand algorithms and models off into the cloud serving stack and partner with mission and payload teams to define requirements and acceptance criteria.
• Own verification and validation, including unit, integration, and performance regression tests.

Skills

PyTorch

Python

Image processing

ML systems

Low-latency

Cloud AWS

Linux

Education

Bachelor's or Master's in CS/CE/EE/Applied Math

Tools

Docker

Kubernetes

CUDA

Job description

Muon Space in San Jose, CA is expanding its HPC team to design and implement image processing algorithms powering ground and flight products. This role focuses on low-latency ML models, edge deployment, and data engineering foundations, with hybrid on-site work three days a week.

Work with mission and payload teams to advance cloud and edge compute for space missions, and contribute to production systems with robust verification and evaluation processes.