OnPeak delivers high-resolution, probabilistic weather intelligence, translated into business impact and paired with expert-in-the-loop guidance, so our customers can manage that risk with confidence.

Organization Type

Organization Size

Funding Stage

Focus: Mitigation or Adaptation

Is this a climate-focused organization?

Sectors

Climate Solutions

industries

remote_preferences

Please provide a link to where you currently list your jobs. If you have a "Careers" page on your website, please list that URL.

Want us to tweet your job? Please write your organization's twitter username below (just the username, please do not add the '@')

Network:

I agree to the terms of use and privacy policy

Weather decision intelligence for high-consequence industries

Overview This is the most senior individual-contributor engineering role at OnPeak. You own how frontier science becomes a reliable, scalable, cost-efficient product — starting with the data model and the ontology everything else is built on. You own the technical foundation: the architecture, the platform, and the standards. This is a true 0→1 architect role — a hands-on, deeply technical position where the decisions you make in your first months become the substrate the company runs on for years. You’ll work in close collaboration with the science organization to deliver a world class product development and deployment environment.What you'll own<ul><li>The data model and data ontology. How we represent weather, fire, terrain, fuels, utility assets (spans, poles, circuits, feeders), forecasts, ensembles, uncertainty, and decisions in one coherent, versioned, queryable system. This is foundational, and it's yours.</li><li>End-to-end platform architecture. Ingestion of continental NWP, orchestration of the downscaling → fire-spread → decision-product pipeline, and delivery to utility customers — running production-grade on AWS.</li><li>MLOps and scientific compute. GPU and HPC workflows (ML diffusion downscaling, WRF-SFIRE, deep learning weather models), batch and near-real-time execution, reproducibility, and cost governance.</li><li>Data infrastructure at scale. Large geospatial-temporal datasets, catalogs, lineage, and the tooling that keeps them fast and trustworthy.</li><li>Reliability, observability, and security to the standard utilities require of an operational decision system.</li><li>Engineering standards and technical culture — you set the bar for how we build and mentor the engineers who join.</li></ul>In your first 6–12 months<ul><li>Establish the canonical data model / ontology and get the team aligned on it.</li><li>Take the pipeline that runs today in research mode and stand up a production-grade version.</li><li>Deploy first production pipeline for pilot customers</li><li>Establish sound training and inference pipelines for AI based modeling: downscaling techniques and ML emulators</li><li>Explore ways of GPU-acceleration of our models to reduce costs and improve inference times.</li><li>Support architecture and design of DoD and NSF grants for advanced ML and physics based modeling.</li><li>Set the technical direction and standards the first engineering hires will build against.</li></ul>You likely have<ul><li>Deep experience architecting production data/ML systems at scale, ideally over geospatial-temporal or scientific-computing data.</li><li>A track record treating data modeling, ontology, and schema design as a first-class discipline — not an afterthought.</li><li>Cloud-native architecture fluency (AWS strongly preferred), orchestration, and infrastructure-as-code.</li><li>Experience with GPU / HPC / scientific or ML pipelines.</li><li>Real 0→1 experience as a hands-on technical leader — setting architecture and raising the bar for the engineers around you.</li></ul>Bonus skills<ul><li>Weather, climate, energy/utility, or geospatial domain background.</li><li>Experience productionizing research models (NWP, simulation, CFD) into services.</li><li>Familiarity with formats and tooling like Zarr, NetCDF, GRIB, COG, GeoParquet, Xarray, Dask, and Kubernetes.</li></ul>Compensation$200,000–$275,000 base salary, plus founding-level equity, set by experience level and location. Benefits include health insurance, unlimited PTO, and 401k matching.About OnPeak IntelligenceOnPeak is a weather-intelligence company building the physics-and-AI forecasting stack that electric utilities need to operate safely as wildfire risk escalates. We pair coupled fire–atmosphere simulation with AI weather prediction and physics based numerical weather prediction with utility-grade decision products that turn probabilistic forecasts into operational calls — where to de-energize, where to pre-position crews, how to defend a span.We're an early-stage, venture-backed team with federal research grants from DoD and NSF, active customers and pilots across the country. Every early hire here is an architect and a builder — you'll define foundations, not inherit them.

Founding Software Engineer , Principal

OnPeak Intelligence

Company Description

Sectors

Email me jobs from OnPeak Intelligence

Sectors

Email me jobs from OnPeak Intelligence