- Research, prototype, and ship core parts of the geospatial engine at the heart of Paces — large-scale spatial search and analysis that energy developers depend on.
- Take open-ended, hard problems in computational geometry and performance — over tens of millions of parcels and nationwide infrastructure data — from prototype to production.
- Work across the full spatial stack: DuckDB, Arrow/GeoArrow, file-based spatial indexing, and a OLTP-backed data lake.
- Explore the frontier of geospatial computation — for example geospatial embeddings and foundation models (e.g. Clay) — and decide what's worth bringing into the product.
- Set the bar for correctness and performance on a system where wrong or slow answers carry real cost.
- 4+ years of experience building data intensive software in a similar role
- Strong computer-science fundamentals: data structures, algorithms, graph theory, and a feel for where time and memory go.
- Fluency in a systems/backend language.
- A track record of building performant, correct backend systems — you can reason about a hot path and read a query plan.
- Experience with DuckDB, Apache Arrow, or comparable columnar/analytical data systems.
- A research mindset: comfort with open-ended problems, prototyping to learn, and knowing when to harden a prototype into a production system.
- Comfort owning ambiguous problems end-to-end and communicating tradeoffs clearly in writing.
- Correctness and performance matter to you. You measure before you claim, document your tradeoffs, and prefer a loud failure to a plausible wrong answer.
- You have real depth in the fundamentals and reach for the right primitive, not the familiar one.
- You operate with high agency — you scope ambiguous problems, decide, and own the outcome.
- You're pragmatic: you ship the simplest thing that solves a real problem.
- Experience with a systems language — Rust, C, C++, Zig, or similar.
- A geospatial / GIS background: PostGIS, GDAL/raster drivers, GeoArrow, projections and coordinate systems, or computational-geometry libraries (GEOS, georust/geo).
- ML, embeddings, or geospatial foundation models (e.g. Clay).
- Familiarity with zarr / GeoZarr or other large-scale array/raster formats.
- Large-scale spatial pipelines, spatial indexing, or distributed/ephemeral compute.
- Open source contributor.
- $150K - $220K annual compensation
- Competitive equity compensation
- 401(k) matching
- Health, Dental and Vision insurance
- Paid company holidays & PTO
- Hybrid work in the office in Williamsburg, Brooklyn ~3x per week
- 🛠️ If you’re a builder who wants to actively construct a more climate positive future, join us!
- 🗺️ We are enabling the climate optimum use for all the world’s land and are thought leaders in the evolving data center and renewables markets.
- 🐶 We have a dog calendar and have dogs running around in the office.
- 🌞 We have world class customers and are growing!
- 📢 We've raised $18M+ led by Navitas Capital, Resolute Ventures and Y Combinator.
Skills Required
- 4+ years building data intensive software in a similar role
- Strong computer-science fundamentals: data structures, algorithms, graph theory
- Fluency in a systems/backend language
- Track record of building performant, correct backend systems; ability to reason about hot paths and read query plans
- Experience with DuckDB, Apache Arrow, or comparable columnar/analytical data systems
- Research mindset: comfortable with open-ended problems, prototyping to learn, and hardening prototypes for production
- Comfort owning ambiguous problems end-to-end and communicating tradeoffs clearly in writing
- Experience with systems languages such as Rust, C, C++, or Zig
- Geospatial/GIS background: PostGIS, GDAL/raster drivers, GeoArrow, projections, GEOS, or georust/geo
- Experience with ML, embeddings, or geospatial foundation models (e.g., Clay)
- Familiarity with zarr / GeoZarr or other large-scale array/raster formats
- Experience with large-scale spatial pipelines, spatial indexing, or distributed/ephemeral compute
- Open source contributions
What We Do
Energy demand is skyrocketing, and renewable energy is the most scalable path forward. But today’s development process can’t move fast enough to meet global goals. Paces exists to change that. We are building software and services to accelerate renewable energy deployment and lower costs - unlocking one of the greatest opportunities of our time: transforming how infrastructure gets built and ensuring it’s built with renewable energy. Paces automates early-stage due diligence and provides the expertise to accelerate late-stage diligence, fast-tracking projects from siting to construction-ready. Our platform supports renewable energy and data center developers, real estate firms, and more by streamlining siting, interconnection, and permitting. With Paces, teams can de-risk decisions, shorten timelines, and get more renewable energy projects built.
Gallery


.png)






