Senior Robotics AI Engineer

Summary

Our team leverages state-of-the-art AI to better understand and communicate with users via semantic and contextual intent understanding. We are looking for a Robotics AI Engineer to bring frontier reasoning and multimodal models to life in real-time, interactive experiences.

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)

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.

Responsibilities

Use frontier reasoning models to map user intent into robust, closed-loop plans that clarify, adapt and replan as the encompassing context changes Build agent harnesses that ground model reasoning in the user's context and a structured set of system capabilities Leverage multimodal models to understand user intent across audio, text & vision Evaluate models by translating product requirements into the right set of metrics, and use them to systematically identify failures and drive improvements Fine-tune and distill frontier models into smaller, efficient models for on-device use Deploy and optimize models on Apple silicon for real-time, efficient and interactive performance Rapidly prototype and assess the latest AI models, tools, and agent harnesses to advance product capabilities