GenAI Research Engineer

Do you believe that generative models can fundamentally change how people interact with devices? Are you excited by the possibility of connecting people to unprecedented levels of creativity? Come join the team that turned cutting edge Generative AI research into compelling user experiences through Apple Intelligence. We are part of the Intelligent System Experiences team at Apple and work on the core modeling technology behind Genmoji, Image Playground and Image Wand.

From web-scale datasets to distributed training of foundation models, application specific adapters to on-device optimizations, you will have the unique opportunity to advance and ship state-of-the-art technology that impacts Apple users around the world!

Description

We're looking for a Research Engineer to make these models dramatically faster, smaller and cheaper to run on-device and on server.

You'll work across the whole efficiency stack:

Develop and deploy optimizations algorithms to speed up inference of our production diffusion models (PTQ, QAT, kernel fusion, model distillation).

Design hardware-aware architectures that fit within compute and memory limits with minimal loss of quality.

Own the process end-to-end from prototyping, evaluation to deployment into the Apple ecosystem.

Minimum Qualifications

• M.S. or PhD in Computer Science or a related field such as Electrical Engineering, Robotics, Statistics, Applied Mathematics, or equivalent experience.
• Deep, demonstrated expertise in at least one of: Quantization (low-bit and mixed-precision methods, quantization-aware training).
• Efficient architecture design, structured pruning or neural architecture search for GenAI or Vision applications.
• Strong hands-on experience training and fine-tuning diffusion or other large generative models in PyTorch, JAX, or an equivalent framework.
• Comfortable reasoning about efficiency beyond FLOPs, such as memory, latency and numerical precision, and eager to learn hardware-specific constraints.
• Excellent cross-functional collaboration skills: You can explain model trade-offs to hardware engineers, hardware constraints to researchers, and integration needs to software teams, in writing and in person.

Preferred Qualifications

• Publications at CVPR, ICCV, NeurIPS, ICML, ICLR or MLSys on efficient generative models, or significant open-source contributions in this area.
• Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan.

You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.

Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.