Machine Learning Engineer, Intelligent Sensing Technology Incubation

Imagine what you could do here. At Apple great ideas have a way of becoming great products services and customer experiences very quickly. Bring curiosity passion and dedication to your job and theres no telling what you could accomplish! nnOur Camera Incubation team is a multi-disciplinary team responsible for looking down the road and prototyping new experiences architectures and technologies. We collaborate with design and product teams to bring new features across the Apple product line. Join us as together we explore concept prototypes helping shape what intelligent cameras can sense understand and doand the experience they create for the people who use them.

Were looking for a creative ML Research Engineer to join our incubation team where youll work across the full stack from model training and systems integration to rapid prototyping. While working on a diverse portfolio of exploratory projects youll bring deep practical knowledge of ML/AI architectures and multimodal sensing applied to physical spaces paired with a design-centric approach to moving ideas from experiment to integrated system. The ideal candidate is energized by open questions comfortable navigating ambiguity quick to reorient when new data shifts the direction and always able to clearly articulate the motivation tradeoffs and risks behind their approach.

BS and a minimum of 3 years relevant industry experience in machine learning or AI engineeringnFamiliarity with state-of-the-art architectures including transformers reinforcement learning and predictive inferencenStrong coding skills across modern ML frameworks (e.g. PyTorch) with a practical approach to tooling that includes AI-assisted development as a natural part of the workflownProven experience building end-to-end ML pipelines from data acquisition and preprocessing through training evaluation and deploymentnExperience architecting and integrating sensing systems that fuse multimodal signals (e.g. vision audio IMU LiDAR) with ML models running on mobile wearable or robotic platforms

MS or PhD with substantial applied research experience in a relevant areanAbility to clearly communicate technical tradeoffs risks and rationale to both technical and non-technical collaboratorsnDemonstrated comfort with ambiguity and a track record of adapting quickly when direction shiftsnExperience working in a research incubation or early-stage exploratory environmentnFamiliarity with on-device or edge ML deployment and its associated constraintsnBackground in robotics embedded systems or real-time sensing pipelinesnKnowledge of practical Bayesian reasoning and methods nExperience with physics-based machine learning including physics-informed neural networks simulation-to-real transfer or learned physical modelsnCross-disciplinary collaboration experience hardware software design and research