Staff Software Engineer, Machine Learning (Computer Vision)

About DeepWalk

DeepWalk is a fast-growing venture that helps cities keep people safe using computer vision to map and monitor their sidewalks. We have ongoing contracts with cities, universities, and engineering firms.

In the past year, we’ve processed thousands of miles of sidewalk across 20+ states, generating millions of labeled data points used in real-world infrastructure decisions. We’ve raised $4.1M, recently closed a $2.1M seed round led by Enable Ventures, and we currently generate 7-figure revenue helping communities across America.

Staff Software Engineer — Computer Vision Platform

We’re hiring a Staff Software Engineer to lead the technical direction of DeepWalk’s computer vision platform for automated sidewalk inspection. This role is focused on tackling high-impact, open-ended problems around large-scale imagery, production ML systems, and data pipelines that handle hundreds of terabytes of data. We’re specifically looking for engineers who have built and operated computer vision or ML systems in production at scale (not just research or prototyping).

You’ll play a key role in how we process, analyze, and deliver insights from millions of images, supporting cities as they work to build safer, more accessible infrastructure.

In this role, you’ll work closely with a handful of experienced engineers, help set technical direction, and establish patterns the team can scale with.

Our core stack today includes Python-based CV/ML systems running on AWS, with data pipelines and services designed to handle large volumes of imagery and geospatial data.

What You’ll Do

As a Staff Engineer at DeepWalk, you’ll have significant ownership over both the systems we build and how we build them. You will…

• Own the lifecycle of our computer vision models, including training, evaluation, deployment, and iteration
• Improve model performance in real-world conditions (noise, edge cases, data drift)
• Design and improve data pipelines that process thousands of miles of sidewalks and millions of images
• Lead architectural decisions for handling hundreds of terabytes of geospatial and visual data, including storage layout, pipeline reliability, and inference performance
• Set and evolve best practices around deployment, observability, system reliability, and scalability
• Act as a senior individual contributor and mentor, helping raise the technical bar across the engineering team
• Work closely with the CEO and operations team to turn business needs into clear technical priorities

What Success Looks Like (First 3–6 Months)

• Build a strong understanding of our current computer vision systems and data pipelines
• Identify the biggest scaling, reliability, and maintainability gaps as we grow
• Propose and begin executing on a clear plan to improve how we deploy, monitor, and operate production ML systems
• Become a trusted technical partner to leadership

What We’re Looking For

Required

• 6+ years of experience, including direct ownership of production ML or computer vision systems (training, deployment, and ongoing operation) Experience taking models from training → production → monitoring → iteration in a real-world environment
• Experience owning system architecture and influencing technical decisions across teams
• Experience deploying computer vision or ML systems in real-world production environments
• Fluency in at least one modern backend language (Python, Java, TypeScript, Go, etc.)
• Strong understanding of system design, scalability, and distributed systems
• Experience with cloud platforms such as AWS, GCP, or Azure
• Comfort working in a startup or growth-stage environment with changing requirements

Nice to Have

• Experience with large-scale or real-time data pipelines
• Infrastructure-as-Code experience (Terraform, CDK, etc.)
• ML observability, data validation, or model deployment experience
• Familiarity with geospatial, imagery, or sensor-driven data
• An interest in urban planning, accessibility, or civic technology