Loft's AI for Space group is building the stack that runs real machine learning in orbit; turning raw sensor data into decisions on the satellite itself, so insight reaches the customer in minutes instead of hours.
The AI Engineering team is where models meet the spacecraft. We own the full path from a partner's trained model to something that actually runs — fast — on flight hardware: compiling ONNX models into optimized engines for each accelerator, the Space Inference Engine and its execution providers, the SDK that packages models for flight, and the perf tooling that proves a model fits its power, thermal, and latency budget before it ever leaves the ground. As we open the platform to a growing roster of defense and Earth-observation partners, the team's scope and the range of silicon we target are expanding fast.

As our ML Runtime Engineer, you'll own model compilation and the performance tooling behind it. We're looking for someone scrappy — the kind of engineer who takes an unfamiliar model and an unforgiving power budget, digs into the graph, and gets it running on real hardware without waiting for the path to be handed to them. You'll move between model compilation, runtime internals, quantization, and hardware-in-the-loop CI, sometimes in the same afternoon.

 *Research shows that while men apply to jobs where they meet an average of 60% of the criteria, women and other underrepresented people tend to only apply when they meet 100% of the qualifications. At Loft, we value respectful debate and people who aren’t afraid to challenge assumptions.  We strongly encourage you to apply, even if you don’t check all the boxes.