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Boston, Massachusetts, United States
Onsite
The best infrastructure is invisible. You only notice it when it fails. For decades, the people responsible for our roads, bridges, and sidewalks have been asked to manage the physical world with tools that can't see it.
CYVL is the Physical AI company changing that. We help governments build infrastructure faster with hardware, software, and AI — turning street-level capture into living intelligence that 500+ cities and towns across the country use to see what's out there, direct the work, and fix problems before they fail.
We believe in a future where infrastructure keeps up with society. Every street, sidewalk, bridge … everywhere. The proof isn't a dashboard. It's a smoother commute, a safer walk to school, public dollars going where they matter most.
We're a fast-moving team in Boston building for the real world. If you believe technology's highest calling is public good, come build with us.
You'll join the Data Operations team — the group that turns raw street-level capture into the map layers 500+ cities rely on. Every day, sensor data from the field flows through our processing pipelines and comes out the other side as road conditions, sidewalk inventories, sign catalogs, and pavement scores. You'll own pieces of that pipeline: running deliveries end to end, catching the data problems before a customer does, and writing the scripts that make the next delivery faster than the last.
Process customer deliveries end to end. Run geospatial data through our Python pipelines, validate the output, and publish the final layers to the Cyvl platform
Build QC checks to review data automatically
Investigate failed and stalled processing jobs in our AWS pipelines, find the root cause, and document the fix
Automate recurring manual steps into repeatable scripts and runbooks, and measure the time saved
Partner with engineering and customer success to turn field-reported issues into resolutions either by code fixes or process improvements
Currently pursuing a degree in Computer Science, Data Science, or a related field
Proficient in Python. Comfortable writing scripts that read, transform, and validate data
Comfortable working in a terminal and with version control
Available full-time for 10–12 weeks in Summer 2027, based in our Boston (Somerville) office
GIS experience (QGIS or ArcGIS, and geospatial formats like GeoJSON, shapefiles, GeoPackage)
Familiarity with cloud infrastructure, especially AWS
SQL and experience querying real datasets
Exposure to geospatial Python libraries (geopandas, shapely)
Interest in civic infrastructure, transportation, or public-sector technology
A knack for the business side. You think about how data drives decisions, and you're drawn to solving problems like "how do we track this better" or "how do we make this visible to the team"
Experience building dashboards or aggregating data into something a non-technical person can act on
Our values guide how we operate:
Real - authentic, transparent, focused on solving real problems with simple, effective solutions.
All Out - bold, driven, and committed to delivering results that matter.
Accelerating with Intention - always learning, growing, and moving with intention.
Reliable - we follow through and deliver at a consistently high bar.
Empowering - we lift each other up and help governments build infrastructure they can be proud of.
Learn about our startup journey
Together, we stay curious, learn quickly, and keep raising the bar. If you want to grow, make an impact that truly matters, and be part of a team that’s shaping the future of public infrastructure, you’ll feel right at home at Cyvl.
Want to go the extra mile? (Optional)
If you're excited about this role and want to tell us more, email dataopsintern@cyvl.ai with the subject line "Data Ops Intern – [Your Name]" and answer any or all of these:
Why Cyvl, and why a startup? What draws you to this kind of work, and to a small team where your work ships right away?
What's the coolest thing you've built with AI? A class project, side project, script, or experiment all count. Tell us what it did and what you learned.
Tell us about a time you solved a problem by fixing the process instead of just working harder. What was slowing you down? What did you change? What happened?
A few honest paragraphs beat an AI-slop essay. Links to code, notebooks, or demos are welcome.
At Cyvl, we welcome diversity in all forms. We do not discriminate based on race, color, religion, sex, gender, sexual orientation, age, national origin, disability, veteran status, or any other protected characteristic.
