iPhone is the most popular camera in the world. The flawless integration of software and hardware has led to features like Memories and Portrait Mode that delight hundreds of millions of users. The Camera & Photos team shapes these experiences by applying machine learning, computer vision, and image processing at scale, and shipping it to production on devices used by millions.
The Camera Intelligence team builds the ML systems and algorithms behind Apple's mobile imaging experiences, from iPhone to iPad. We're looking for a senior ML engineer who can take a research idea all the way to a shipping, on-device feature: someone equally comfortable pushing the state of the art and making it run fast, efficiently, and reliably in production.
Description
You will apply your ML and computer vision expertise to build, evaluate, and ship models that power Apple's imaging experiences, turning early-stage ideas into commercially viable, efficient, on-device algorithms. You'll stay current with developments across computer vision, deep learning, and adjacent ML fields (including LLMs and multimodal models where relevant), and use that knowledge to influence technical direction across the team and Apple's products.
Minimum Qualifications
10+ years of combined research and hands-on engineering experience building and shipping ML systems, ideally with a strong foundation in computer vision.
Proven track record productizing ML research: taking models from prototype to on-device deployment, including optimization, quantization, and other techniques for efficient inference at the edge.
Experience designing and scaling ML pipelines against large, real-world datasets.
Demonstrated technical leadership: setting technical direction, driving cross-functional initiatives, and mentoring other engineers/researchers.
Depth in one or more of: image processing, optical flow, object tracking/registration, generative models, or modern deep learning architectures. Experience with NLP, LLMs, or vision-language models is a strong plus.
Strong software engineering fundamentals: programming, debugging, and system design.
Excellent problem-solving, critical thinking, and cross-functional communication skills.
Preferred Qualifications
Fluent in modern ML frameworks, with strong hands-on experience in PyTorch, and proficiency with the core scientific/imaging Python stack (NumPy, Pandas, OpenCV, Pillow, or similar).
Experience optimizing models for on-device/edge inference (quantization, pruning, distillation, or deployment on accelerators such as the Apple Neural Engine) is a strong plus.
Proficiency in C++ or Objective-C is a plus.
