Staff Software Engineer Machine Learning (Computer Vision) Remote

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

$150000 – $190000 base salary + equity · Remote

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

Compensation & Benefits

• $150000 – $190000 base salary based on scope and experience

• Equity

• Unlimited PTO (most of our team takes 3–4 weeks per year)

• Health insurance

• 401(k) with ~4% match (100% on first 3% 50% on the next 2%)

DeepWalk participates in the federal E-Verify program to confirm the employment eligibility of all newly hired employees.

DeepWalk is an Equal Opportunity Employer and is committed to building a diverse and inclusive workplace. We do not discriminate on the basis of race color religion sex (including pregnancy sexual orientation or gender identity) national origin age disability genetic information veteran status or any other legally protected status.

In accordance with applicable laws DeepWalk provides equal pay for equal work and complies with all federal state and local pay transparency and compensation requirements.

What We Do

DeepWalk has built an AI-driven platform that measures 3D models of infrastructure and creates useful deliverables for engineering planning and maintenance teams. Over 100 cities across America rely on DeepWalk’s software for measuring planning and updating infrastructure starting with sidewalks. Creating 3D models of buildings and infrastructure has become affordable and widespread. However extracting useful information from models is extremely challenging. DeepWalk’s platform consumes 3D models measures them and outputs the deliverables required to maintain large assets. DeepWalk’s first product generates and measures 3D models of entire sidewalk networks using iPhones or higher-fidelity LIDAR sensors; it’s 10x faster than the current state-of-the-art. Then it creates work orders plans and construction docs 1000x faster and 10x cheaper. All information is stored and displayed in DeepWalk’s subscription web platform and integrations.

Why Work With Us

We spun out of the University of Illinois at Urbana-Champaign in 2019. Since then we've raised over $4M in venture capital and are growing rapidly. Aiming to raise our Series A in 2026 to expand beyond iPhone data collection and into different inspection verticals.