LLM Engineer — AI Research to Real-World Impact

Apple Inc.; Seattle (WA); On-site; USD 185,000 - 325,000; Full time

Job summary

Apple Inc. in Cupertino, California, seeks a LLM Machine Learning Engineer to advance models and agent science for on-device and server-based Apple Foundation Models.

You will join a collaborative team of software engineers and researchers focused on large language modeling, optimization, interpretability, and related algorithms, translating promising ideas into Apple products. Successful candidates bring strong software engineering, hands-on ML development, and experience with post-training

Qualifications

• Define goals and deliver results in AI product development.
• Read, evaluate, and reproduce recent research for practical use.
• Experience optimizing or post-training LLMs and model sensory tests.
• Strong Python and UNIX skills with agentic coding tools.
• Applied research in neural network optimization or training.
• Proven track record balancing research and real-world constraints.

Responsibilities

• Build groundbreaking ML capabilities and drive emerging innovations.
• Join a team of developers and deep learning experts focused on LLMs.
• Translate ideas into Apple product context and ship at scale.
• Lead experiments and ablations to improve models under constraints.

Skills

Goal setting under uncertainty

Research evaluation

LLM optimization

Python

UNIX

Agentic coding tools

Experimentation in ML

Communication & collaboration

Education

BS + 5+ years

MS + 3+ years

PhD + 1+ year

Tools

Python

UNIX

Job description

Apple Inc. in Cupertino, California, seeks a LLM Machine Learning Engineer to advance models and agent science for on-device and server-based Apple Foundation Models.

You will join a collaborative team of software engineers and researchers focused on large language modeling, optimization, interpretability, and related algorithms, translating promising ideas into Apple products. Successful candidates bring strong software engineering, hands-on ML development, and experience with post-training