Principal Software Engineer, Matroid

• You bring deep expertise in at least one of these areas and can demonstrate clear success and impact in your prior experience
• 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

Desirable

• 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
• 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