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.
Senior/Staff Software Engineer — Computer Vision Platform
$150,000 – $190,000 base salary + equity · Hybrid (Chicago)
We’re hiring a Senior/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 ML or computer vision 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
5+ 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 environmentExperience owning system architecture and influencing technical decisions across teams
Experience deploying 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
$150,000 – $190,000 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%)
Convenient office location in The Loop
Hybrid work environment (typically 2 days in-office)
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.
