AI Engineer

Build and operate machine learning models for sales roleplay, scoring, and coaching products, owning the lifecycle from fine-tuning and evaluation through production and on-device deployment. The role emphasizes open-source models, latency and privacy optimization, and rigorous model testing.

Build and deploy algorithmic systems for high-impact healthcare problems, choosing among machine learning, optimization, heuristics, and hybrid approaches. The role requires 4+ years of relevant industry experience, strong applied problem-solving and evaluation skills, and fluency in modern ML tooling.

Build research infrastructure and tooling that enables AI models to design silicon, including reinforcement learning environments, EDA integrations, evaluations, and experiment workflows. The role requires strong software engineering fundamentals and comfort working across research, tooling, and chip-design systems.

Build and optimize the production LLM inference runtime for frontier models on OpenAI’s custom silicon. The role spans scheduling, distributed execution, memory and KV-cache management, performance tooling, and hardware-software co-design.

Build and operate production machine-learning systems for content safety, from messy customer data through classification, evaluation, and inference. The role requires 5+ years of ML engineering experience, strong Python and MLOps skills, and sound judgment across classical models and LLMs.