Principal Software Engineer

We’re looking for a Principal Software Engineer to help build the next generation of Matroid’s computer vision platform, shaping its architecture and technical direction.

You’ll lead complex initiatives from definition through production, solve problems spanning computer vision, deep learning and infrastructure, and make the engineers around you more effective. You bring deep expertise in at least one of these areas and can demonstrate clear success and impact in your prior experience.

This is a hands-on role with broad technical and organizational influence.

• →Lead major initiatives spanning software, infrastructure, deep learning, and computer vision - from ideation and research through development, deployment, and iteration
• →Keep up with latest capabilities in a fast-moving field and how best to incorporate them in our user-facing platform to solve real-world problems
• →Turn ambiguous goals into pragmatic designs, milestones, and clear ownership
• →Make consequential architectural decisions balancing velocity, reliability, maintainability, performance, and cost
• →Raise the effectiveness of other engineers through technical direction, delegation, review, and mentorship
• →Personally prototype, code, and debug high-leverage problems without becoming the team’s bottleneck
• →Identify and remove recurring barriers to engineering execution

• Owning real-world production outcomes with high autonomy
• Leading through technical judgment, clear communication, and example
• Diagnosing problems across models, software, infrastructure, hardware, and data
• Knowing when to build a platform versus a focused solution; balancing short- and long-term velocity and risk

• Deep expertise in either computer vision and deep learning or production systems and infrastructure
• Passion for learning new things; happy working across different parts of the stack and wearing different hats
• Demonstrated success building substantial technical systems alongside multiple engineers
• A track record of making sound architectural decisions and evolving complex systems pragmatically
• Significant recent experience designing systems, writing production code, and debugging difficult cross-system failures
• Strong communication skills, particularly when framing technical decisions and tradeoffs

• You have led engineers across both machine learning and infrastructure
• You have experience with GPU systems, distributed systems, Kubernetes, AWS, MLOps, or production computer vision
• You have hired or managed engineers while remaining deeply technical
• You have significant open-source contributions, publications, or other public work demonstrating your impact in the field