ML Research Engineer

ML Research Engineer

Video is at the core of nearly all Apple products, and as a research engineer on our team, you will build the infrastructure, pipelines, systems, and models that power the next generation of video technology. We are looking for a highly ambitious individual, who will flourish working on technically meaningful problems across the full ML lifecycle — including training infrastructure, performance optimization, data, and production deployment. Your work will redefine the video experience for billions of users.

In this role you will work together with colleagues to design, scale, and harden the systems that bring ML-based video approaches into current and future Apple products. This position requires a highly self-directed individual, who is comfortable working at the intersection of ML, systems engineering, and performance optimization. Strong engineering and analytical skills will be critical towards solving challenging problems across efficiency optimization, training, data, and deployment.

• Design, build, test, and scale ML systems: training infrastructure, data ingestion and curation pipelines, power and performance optimization for inference, ML model development
• Collaborate closely with team members and cross-functional teams to achieve quality, throughput, computational requirements, and robustness towards shipping the technology
• Communicate: demonstrate the technology, present to leadership, share progress with colleagues, and so on

• BS and 10+ years of hands-on industry experience building production ML systems, with a proven track record of design/implementation leadership
• Deep familiarity with in of ML-centric flows and best practices: training procedures, dataloaders, profiling and debugging methodology, data handling, model development, model deployment
• Proficiency in Python, C++, PyTorch
• Familiarity with computer architecture principles
• Proficiency in AI tooling such as Claude and excellent high-level design skills — allowing building robust, modular, clean, and well-tested code

• MS specializing in ML systems, performance engineering, or a related area
• Experience implementing custom ops in CUDA or low-level GPU kernel optimization
• Research experience in ML model design
• Experience with visual data (e.g. images/videos/3DGS) and related vision algorithms
• Experience with distributed training, large-scale data pipelines, inference serving
• Excellent written and oral communication skills

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 $184,700 and $324,800, 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.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant At Apple, we believe accessibility is a fundamental human right. You'll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong. Learn about accessibility in Apple's workplace Learn about reasonable accommodations for job applicants