<p>Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something. At Apple, we strive to make great products that empower people and improve their lives. We believe recent breakthroughs in AI/ML and robotics have the potential to unlock new experiences that were never possible before, and are looking for talented ML data engineers to realize that mission by expanding the capabilities of Apple products and platforms.</p> <p>As a member of the team, you'll have the opportunity to work with a team of highly skilled engineers and scientists to bring new experiences to Apple products. This position requires a self-motivated ML data engineer with strong technical and interpersonal skills to handle responsibilities including:</p> <p>Familiarity with Swift and Apple developer tools Experience in training/fine tuning multimodal foundational models Experience in building RL models for robotics applications. Experience in multi-view geometry, camera calibration and 3D reconstruction pipelines. Experience optimizing ML models or mathematical algorithms for mobile deployment and resource-constrained environments.</p> <p>MS/PhD in Computer Science, Math, Machine Learning, Robotics, or related fields. 3+ years of relevant industry experience Strong software engineering background Ability to break down large features and implement practical solutions Experience in building complete prototypes that continuously improving the system performance Familiarity with the full robotics stack (controls, perception, planning, navigation etc.) Familiarity with modern ML approaches (VLMs LLMs, Diffusions, RL, etc.) Proficiency using deep learning frameworks such as PyTorch and TensorFlow.</p>