Join us
Work with us
We’re a small technical team in Lausanne, incubated at EPFL, working at the intersection of machine learning, weather, and energy markets. Backed by the EPFL AI Center, the Swiss National Science Foundation, and Innosuisse, with active pilots at European wind operators and trading desks. We work directly with customers on real production data, and look for people who want ownership of hard problems from day one.
Open positions
ML engineer / scientist
ML engineer / scientist
Join us for an internship focused on advancing our local renewable production modelling. You’ll work directly with the founders on research and engineering problems that go straight into the product and into customer pilots.
What you’d work on
- Develop and improve ML models for local renewable production at the asset and portfolio level
- Explore probabilistic methods to quantify uncertainty in production estimates — ensembles, quantile regression, conditional generative models, calibration
- Stay close to recent research in ML for weather and renewables, and prototype new techniques against real benchmarks
- Build and maintain a scalable codebase across large-volume weather, SCADA, and market data — data pipelines, reproducible training, model serving
- Run experiments end-to-end, from hypothesis to deployment, with rigorous evaluation against production data
What we’re looking for
- Strong background in machine learning, ideally with applied experience in time series, spatiotemporal data, or probabilistic modelling
- Master’s-level or PhD candidate in computer science, applied mathematics, physics, engineering, or a related field
- Comfortable in Python (PyTorch in particular), with solid software engineering instincts — clean code, version control, reproducibility
- Experience with large geospatial or weather datasets (xarray, NetCDF, Zarr, Parquet) is a plus
- Background or strong interest in weather forecasting and/or energy markets is highly encouraged
- Self-directed, comfortable with ambiguity, able to drive a problem from research to production
How to apply
Email us your CV. Instead of a generic cover letter, we’d love a few personal answers to the questions below. Short is fine, and you don’t have to answer all of them — they’re just here to help us get to know you.
- What drew you to this role specifically? Why this kind of environment over a larger company or an established team?
- Which of your past projects or experiences feels most relevant to what we do, and why?
- What do you think you could bring to WindLens?
- Tell us about a personal project you’ve worked on. It doesn’t have to be technical or connected to your studies or work — just something you built, made, or pursued on your own.
- What’s one thing about how you think or work that someone who knows you well would say is distinctive about you?
Feel free to share any links (GitHub, blog, project page) that help us see your work.
Send your CV and your answers to matteo.peduto@epfl.ch.
Nothing that fits?
The work touches energy markets, weather, trading, probabilistic modelling, and data infrastructure. If your experience sits anywhere in that space and you’d like to work with us, reach out — tell us what you’d want to build.
Email us