Your role
We are building the forecasting foundation model to rule them all. All enterprise companies run forecasting to plan their operations: staffing, supply-chain management, finances… We provide the data, models and platform to easily build the most accurate forecasts. This significantly reduces waste and increases cash flow for our customers.
The forecasting model is at the heart of our technology. As the founding MLE, you will build, train and deploy large foundation model architectures: implement and combine ideas from the literature, experimentally verify them, and ultimately deploy your model for our customers to use in production. Our goal is for our models to be the best for our customers’ use cases.
You love your craft, have high standards, stay up-to-date with the latest ideas in ML, and know when to make trade-offs to ship. You live and breathe neural networks, speak PyTorch or Jax, and are comfortable with large amounts of data. Bonus if you have experience building solid ML infra.
Your responsibilities
Architect and train time-series foundation models using diverse datasets, integrating multimodal inputs like numerical time series, text, and image data
Stay up-to-date on the foundation model literature
Design reproducible experiments to verify, compare and combine ideas from the literature
Deploy models for use in our API and platform - getting into the gritty details if exporting to ONNX requires some custom operation or torch.compile fails
You’re not afraid to join a customer meeting to learn about their use case, to collaborate with our data engineer on ML data pipelines, or take on other miscellaneous tasks.
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