LLM Machine Learning Engineer, Models and Agent Science, AIML

The Apple Intelligence Agents, Infrastructure, and Research team brings

innovative AI research into Apple products, with a focus on optimizing,

interpreting, and developing new algorithms for on-device and server-based Apple

Foundation Models and Apple Intelligence features.

DESCRIPTION

We are looking for talented Machine Learning Applied Scientists and Research

Engineers to build groundbreaking machine learning capabilities and drive

emerging innovations. You will join a collaborative team of software developers

and deep learning experts focused on large language modeling, optimization,

interpretability, and related algorithms.

In this role, you will

• drive applied
• innovation and evaluate emerging research for real-world viability, translating
• promising ideas into the Apple product context. You'll bridge the gap between
• cutting-edge ideas and the constraints of shipping AI at scale. Successful
• candidates will bring a strong software engineering background, hands-on
• zero-to-one machine learning development experience, and broad expertise in
• post-training machine learning models (including quality and performance
• optimization).
• MINIMUM QUALIFICATIONS
• Proven ability to define goals and deliver results amid uncertainty and
• real-world constraints in AI product development Ability to read, evaluate, and
• reproduce recent research and assess its practical viability under real-world
• constraints Experience optimizing or post-training large language models (LLMs),
• developing interpretability or stress-testing algorithms, steering model
• behavior, or building agent harnesses Strong Python and UNIX skills and a
• demonstrated ability to use agentic coding tools in these environments History
• of applied research in neural network optimization, model training, or a related
• area Proven track record of driving scientific investigations and experiments
• while overcoming obstacles and uncertainty in a research environment BS and 5+
• years of experience, MS and 3+ years of experience, or PhD and 1+ year of
• experience
• PREFERRED QUALIFICATIONS
• PhD in a related field Publication record at top AI/ML venues Experience with
• post-training LLMs and network optimization algorithms, as well as
• interpretability or steering techniques for LLMs Experience of working with
• large-scale compute infrastructure Experience shipping a real world product,
• project or feature Experimental rigor and ablation design when benchmarking LLM
• optimizations Strong communication and accountability skills, with a
• collaborative mindset and strong work ethic