Forward Deployed ML Engineer on the Technical Services team adapting PyTorch deep learning models (CNNs, GNNs, transformers) to specific mines. Role splits 60% applied ML for one mine and 40% foundational ML, with at least 2 mine visits a year. Stack is Python, PyTorch, FastAPI, Pydantic, DynamoDB, AWS, and Azure.
We are looking for a Forward Deployed ML Engineer, with an interest in solving difficult real-world problems to join our Technical Services team.
This role will require extensive working with custom architectures on PyTorch. Previous experience working with PyTorch on complex Convolutional Neural Network, Graph Neural Network, and/or Transformers is expected. This role is equivalent to the Delta team Forward Deployed Engineer role at Palantir that we would recommend you read up on.
This is a remote-first position, with a preference for applicants based in Canada.
We're Stratum, a mining software company with machine learning models as our core product. Our 3D maps predict how gold, silver, copper, etc. are distributed (and how much!) using only small amounts of data, unconventional data processing, and proprietary ML protocols. Our work directly affects how much money a mine is going to make next week/month/year while reducing waste/cost. We're supported by Founders Fund, Aramco, Builders VC, Y Combinator, and Ilya Sutskever, former Chief Scientist at OpenAI, who have recognized the potential of our industry-disrupting technology.
Our long-term vision is to build a massive AI engine capable of making every decision in a mining operation, down to moving individual rocks. If you’re an exceptional engineer interested to helping make this vision a reality we look forward to reviewing your application and working together.
