LLM Machine Learning Engineer
Apple
Job Summary
Apple is seeking an extraordinary engineer to join the Product Operations team as an LLM Machine Learning Engineer. This role involves designing and implementing machine learning strategies for supply chains and building the future of manufacturing systems and smarter factories. You will collaborate with multi-functional teams, apply algorithms to large-scale data, and deliver machine learning solutions from problem conceptualization to deployment. Responsibilities include performing ad-hoc statistical analyses, working with data engineers to generate business intelligence solutions, and presenting analyses to diverse audiences, including executives.
Must Have
- 3+ years of experience in machine learning algorithms, statistics, and data mining models
- 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
- 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
- Ability to meaningfully present results of analyses in a clear and impactful manner
Good to Have
- Proven experience in LLM and LMM development, fine-tuning, and application building
- Experience with agents and agentic workflows
- Experience with modern LLM serving and inference frameworks, including vLLM
- Hands-on experience with LangChain and LlamaIndex
- Familiarity with distributed computing, cloud infrastructure, and orchestration tools
- Deep understanding of transformer-based architectures (e.g., BERT, GPT, LLaMA) and their optimization
- Experience applying ML techniques in manufacturing, testing, or hardware optimization
- Proven experience in leading and mentoring teams
Perks & Benefits
- Comprehensive medical and dental coverage
- Retirement benefits
- A range of discounted products and free services
- Reimbursement for certain educational expenses
- Discretionary employee stock programs
- Discretionary restricted stock unit awards
- Discounted Apple stock purchase
- Discretionary bonuses or commission payments
- Relocation
Job Description
LLM Machine Learning Engineer
- 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 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.
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.