Description
In this role, you will translate natural user intents into robust, adaptive behaviors. You will work across the full stack of applied AI/ML: prompting and evaluating frontier models, distilling them into efficient on-device models, and deploying them on Apple silicon. A successful candidate is energized by rapidly experimenting with the latest AI models, tools, and agent harnesses, and has a strong foundation in modern machine learning with hands-on experience training and fine-tuning their own models. Above all, this is a deeply product-driven team that values engineers who have shipped real products and are motivated by putting great experiences into users' hands.
Minimum Qualifications
BS or MS in Computer Science or Machine Learning Strong background in and deep understanding of modern machine learning methods Experience training or fine-tuning your own transformer and/or diffusion models Proficiency using coding agents such as Claude Code and Codex Genuine excitement for experimenting with the latest AI models, tools, and multimodal capabilities
Preferred Qualifications
PhD in Computer Science, Machine Learning, or a related field Experience with model fine-tuning and distillation for efficient, on-device deployment Hands-on experience with inference engines such as llama.cpp, vLLM, MLX, or Core ML Experience building agent harnesses for multi-step, closed-loop reasoning Track record of shipping products to users Proficiency in Python and ML frameworks (PyTorch or TensorFlow)
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