Machine Learning Engineer- LLM
The people here at Apple don’t just build products — they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that encourages 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.
Imagine what you could do here. At Apple, new insights have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish.
With the growth of Apple, we have created new opportunities for individuals to work on the most exciting new products introduced by Apple. We are seeking individuals who meet the following criteria to join us. This position will work closely with various operations & engineering teams to create and develop innovative solutions via Machine Learning (ML) development to improve production quality and efficiency.
Responsible for leading test & inspection station design, development, and solution via machine learning with excellent reliability and scalability for operations
Responsible for leading all the ongoing factory test & Inspection processes and procedures, for new product introduction from prototype to mass production.
- 3+ years of experience in machine learning algorithms, software engineering, and data mining models with an emphasis on large language models (LLM) or large multimodal models (LMM).
- MS/PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering, or related field.
- Good communication skills with proficiency in spoken and written English and Chinese.
- 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, and 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.