LLM Machine Learning Engineer, Models and Agent Science, AIML

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

LLM Machine Learning Engineer, Models and Agent Science, AIML

Cupertino, California, United States Machine Learning and AI

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

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

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