Machine Learning Engineer- LLM

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.

Description 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.

Minimum Qualifications

• 3+ years experience in machine learning algorithms, software engineering, and data mining models with an emphasis on large language models (LLM) or large multimodal models (LMM).
• Masters in Machine Learning, Artificial intelligence, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering or related field.

Preferred Qualifications

• 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 LangChain and LlamaIndex, 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, TensorFlow, 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.

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 $175,800 and $264,200, 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.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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.