LLM Machine Learning Engineer

Cupertino, California, United States Operations and Supply Chain

Imagine what you could do here. At Apple, we believe new insights have a way of becoming excellent products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts.

Join Apple, and help us leave the world better than we found it. It takes deeply dedicated, intelligent individuals to maintain and exceed the high expectations  Product Operations team is looking for an extraordinary engineer to join our team. You will help design and implement our machine learning strategy to the substantial supply chain and help build the future of our manufacturing systems and smarter factories.

We will be collaborating and working with multi-functional teams and applying algorithms to large-scale data.

Product Operations partners with a variety of different engineering and operations teams, our team leads development of machine learning solutions. We deliver projects from end-to-end: problem statement and conceptualization, proof-of-concept, and participation in final deployment! You will also perform ad-hoc statistical analyses. You will also work closely with data engineers to generate detailed business intelligence solutions. You will be expected to conduct presentations of analyses to a wide range of audiences including executives.

• 3+ years of experience in machine learning algorithms, statistics, and data mining models, with an emphasis on large language models (LLM) or large multimodal models (LMM).
• Master’s degree in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering, or a related field.

• Proven experience in LLM and LMM development, fine-tuning, and application building. Experience with agents and agentic workflows is a major plus.
• Experience with modern LLM serving and inference frameworks, including vLLM for efficient model inference and serving.
• Hands‑on experience with Lang Chain and Llama Index, enabling RAG applications and LLM orchestration.
• Strong software development skills with proficiency in Python. Experienced user of ML and data science libraries such as PyTorch, Tensor Flow, Hugging Face Transformers, and scikit‑learn.
• Familiarity with distributed computing, cloud infrastructure, and orchestration tools, such as Kubernetes, Apache Airflow (DAG), Docker, Conductor, Ray for LLM training and inference at scale is a plus.
• Deep understanding of transformer‑based architectures (e.g., BERT, GPT, LLaMA) and their optimization for low‑latency inference.
• Ability to meaningfully present results of analyses in a clear and impactful manner, breaking down complex ML/LLM concepts for non‑technical audiences.
• Experience applying ML techniques in manufacturing, testing, or hardware optimization is a major plus.
• Proven experience in leading and mentoring teams is a plus.

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 $147,400 and $272,100, 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…