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<Confidential - Energy Sector> | Software / ML Engineer | REMOTE | Full-Time We are a small, profitable, bootstrapped company that applies machine learning (ML) to fluid dynamics (FD) systems. We are looking for an engineer to work closely with the founder and form the core of our team. Role * The FD models are developed by a specialized ML team; they’re evaluated in a simulated environment, where a second ML layer decides agent action based on FD model output. * Everything except development of the FD models is under the purview of this role. (You’re absolutely welcome to dive into that; it’s just not a requirement.) * Minimal bureaucracy: we're a tiny team with existing customers. We don't have outside investors to persuade. There's very little friction in going from idea to production. Responsibilities * Build data pipelines to request, transform and store data. (This is a small component of the role.) * Build (statistical / machine-learned) agent actions based on FD model outputs. * Develop an event-driven simulation environment to evaluate FD and agent models. * Work closely with FD team to iterate on FD model based on simulation performance. * Deploy pipelines and trained FD and agent models into production. Capture events and model inference. Skills * Extensive experience (ideally using Python) to build high-availability, complex systems. * Intimate familiarity with the Python scientific data stack. * Experience with "classical" machine learning, such as tree-based models and Bayesian methods. * Nice-to-have: math or physics background. We prefer remote candidates in the US or Canada, but would consider those in the UK and the EU. Write us at confidential.energy@gmail.com.