Machine Learning Engineer

Machine Learning Engineer About the role Deeter Analytics is a privately held investment research and trading firm managing its own capital across public markets. After years of discretionary success, we think we have some unique ways of seeing the market, and we pair sharp human judgment with modern AI to act on them. Some of those ways of seeing the market can be turned into models. We're hiring a Machine Learning Engineer to build them. Reporting to the senior researcher who leads the project, you'll be the hands-on ML person on a new research effort: take an idea from the desk and turn it into data, models, and experiments, then carry it through to something that runs every day and informs how we trade. You'll set up and run your own compute (a GPU workstation or a few cloud instances, not a cluster) and own the whole loop from raw data to a result the team can act on. It's an entry point into a serious seat: no trading experience needed, deep fundamentals required, and the role grows with you as the work proves out. The role is full-time and fully remote, US-based. What you’ll own - The project. A new research effort with a senior lead; from a desk idea and raw data to models, experiments, and a result the team can act on. You own the loop end to end. - The models. Deep-learning models on market data built, trained, ablated, and improved by you, from the first baseline to something that runs every day. - The compute. Your own small GPU setup, local or on AWS: environment, drivers, containers, storage, experiment tracking, cost. Small-scale by design; you keep it running and you keep it cheap. - The evaluation. Leakage-proof validation on time-ordered data, regime-aware testing, honest baselines; knowing the difference between a result that's real and one that's noise, and being able to show which is which. - The reading. Recent work in foundation models, time-series, and RL: read it, reproduce what matters, and write up what you found in a page the team will ac