Apple Inc.
San Diego, California, United States
Description
Product Operations partners with various engineering and operations teams to develop machine learning solutions. We deliver projects from problem statement and conceptualization to proof-of-concept and final deployment. You will perform ad-hoc statistical analyses and work closely with data engineers to generate detailed business intelligence solutions. You will also present analyses to diverse audiences, including executives.
Minimum Qualifications
- 3+ years of experience in machine learning algorithms, statistics, and data mining models, focusing on large language models (LLMs) or large multimodal models (LMMs).
- Master’s degree in Machine Learning, AI, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering, or related fields.
Preferred Qualifications
- Experience in LLM and LMM development, fine-tuning, and application building. Experience with agents and agentic workflows is a plus.
- Familiarity with LLM serving and inference frameworks like vLLM.
- Experience with LangChain and LlamaIndex for RAG applications and LLM orchestration.
- Proficiency in Python and experience with ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, and scikit-learn.
- Knowledge of distributed computing, cloud infrastructure, and orchestration tools like Kubernetes, Apache Airflow, Docker, Conductor, Ray.
- Understanding of transformer architectures (e.g., BERT, GPT, LLaMA) and their optimization for low-latency inference.
- Ability to present complex ML/LLM concepts clearly to non-technical audiences.
- Experience applying ML techniques in manufacturing, testing, or hardware optimization is a plus.
- Leadership and mentoring experience is a plus.