Staff Machine Learning Engineer

The ADP ML Data Platform team enables future Apple intelligent products by providing Apple engineers with cutting edge ML technologies, large scale compute and data systems specifically designed for machine learning.

Strong foundation in machine learning, with hands-on experience across the end-to-end ML workflow - including data preparation, pipeline development, experimentation, evaluation, and deployment

Expertise in building and running large scale distributed systems

Familiarity with modern generative techniques (e.g. transformers, diffusion, retrieval-augmented generation)

Proven experience building and delivering data and machine learning infrastructure in real-world production environments

Familiarity with fine-tuning workflows, model optimization, and preparing models for scalable inference

Familiarity with generative AI and its applications in accelerating and enhancing machine learning workflows

Experience configuring, deploying and troubleshooting large scale production environments

Experience in designing, building, and maintaining scalable, highly available systems that prioritize ease of use

Extensive programming experience in Java, Python or Go

Strong collaboration and communication (verbal and written) skills

Comfortable navigating ambiguity and evolving technical landscapes, especially in fast-moving areas

B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or equivalent practical experience

Preferred Qualifications

Experience in the below is preferred:

Proficiency in one or more ML frameworks

Experience with containerization and orchestration technologies, such as Docker and Kubernetes.

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 $212,000 and $318,400, 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.

Join a team at the forefront of ML infrastructure and generative AI, where data and model workflows come together to enable the next generation of intelligent experiences on Apple products and services. We build robust systems that connect scalable data pipelines with advanced ML workflows, accelerating the development of real-world AI applications. Our work spans the full ML lifecycle, from experimentation to deployment, and you'll play a key role in shaping how AI models are built, optimized, and scaled. We develop a platform for ML data and features that powers advanced GenAI applications. This includes embeddings (generation, evaluation, ANN search, multimodal support), AI Ops, efficient inference, and a modern feature platform designed to streamline experimentation and drive innovation. We're looking for engineers and researchers passionate about generative models, data-centric ML, and intelligent systems across diverse real-world use cases. With the autonomy to experiment, the scale to make an impact, and the support to take ideas from prototype to production, you'll work alongside a world-class team to build intelligent, flexible systems that make ML development faster, more reliable, and more creative.