Principal Machine Learning Engineer

LE130 Unity Technologies SF; Mountain View (CA); On-site; USD 260,000 - 380,000; Full time

Job summary

Unity Technologies SF is seeking a Principal Engineer for On-Device AI Inference & Systems to lead the integration of state-of-the-art multi-modal models into our runtime. You will own the end-to-end inference stack, from exported checkpoints to kernel-level optimizations, delivering interactive frame rates within tight memory and power budgets.

You will shape engineering standards, drive runtime architecture, and mentor a team of senior and mid-level engineers.

Job description

The opportunity

We are building the next generation of AI-driven game experiences, running generative models on-device, right where the players are — on phones, tablets, laptops, and desktops. Our games run inside a modern, browser-native runtime (built on technologies such as WebGPU and WebNN), so the models that power these experiences must be deployed and accelerated entirely within that runtime. As our Principal Engineer for On-Device AI Inference & Systems, you will be the foremost engineering authority on taking state-of-the-art multi-modal models (transformers and diffusion networks) and making them run fast, small, and reliably within that runtime, fully integrated into a production game engine. This is a deeply hands‑on, high-impact engineering role. You will own the inference and integration stack end‑to‑end — from the moment a trained checkpoint leaves research, through export, optimization, and kernel‑level tuning, to a shipped feature running inside the engine at interactive frame rates within a fixed memory and power budget. You will set the engineering standards, drive the architecture of the runtime and integration layers, and mentor a team of senior and mid‑level engineers. Your work directly determines the latency, quality, memory footprint, and battery profile of AI features experienced by players worldwide. This role is for an engineer who is energized by the gap between a research model and a shipping, AI‑based product