Senior ML Research Engineer, Post-Training for Personalization

Apple, Inc.; Cupertino (CA); On-site; USD 216,000 - 394,000; Full time

Benefits offered by this job

Medical and dental coverage

Employee stock programs

Tuition reimbursement

Relocation assistance

Job summary

Apple is seeking a Staff Research Engineer for post-training for personalization in Cupertino. You will develop algorithms that tailor LLMs to individual users across multimodal contexts and agentic experiences, pushing the boundaries of personalization.

Collaborate with system engineers to prototype bleeding-edge techniques, optimize context memory, and scale models with data infrastructure. Strong emphasis on research impact and practical deployment.

Qualifications

• PhD in EE/CS or related field with ML/vision focus.
• Strong ML and Generative Modeling fundamentals.
• Hands-on with pre-training or post-training of LLMs.
• Familiarity with distributed training.
• Proficient in ML toolkits, e.g., PyTorch.
• Publications or OSS contributions demonstrating research impact.

Responsibilities

• Develop novel algorithms for LLM post-training to enable personalization.
• Advance personalized intelligence across multimodal reasoning and context.
• Collaborate with system engineers to prototype bleeding-edge innovations.
• Interface with modeling and data infrastructure teams.
• Translate research into scalable, high-quality experiences.

Skills

Strong ML fundamentals

Generative Modeling

LLM post-training

Reinforcement learning

Distributed training

PyTorch

Publications / OSS contributions

Education

PhD in Electrical Engineering / Computer Science

Tools

PyTorch

Job description

Senior ML Research Engineer, Post-Training for Personalization

Cupertino, California, United States Machine Learning and AI

Do you believe generative models can transform creative workflows and smart assistants used by billions of people? Do you envision a future where AI fundamentally reshapes how people interact with their devices and communicate, delivering experiences personalized to their unique needs and preferences? We are part of Apple's Intelligent System Experience team, where we develop core modeling technologies that translate cutting-edge research into compelling user experiences. Our work spans Apple Intelligence initiatives, including Personalization, Agentic Search, Generative Memories, Visual Generation, and more.

Description

We are seeking a Staff Research Engineer with a strong track record in developing novel algorithms for LLM post-training to advance personalized intelligence. In this role, you will drive research in post-training methodologies that enable models to better understand individual user needs, adapt to personal context, and deliver more relevant, helpful, and personalized experiences. You will work at the intersection of large language models, multimodal reasoning, personalization, and agentic systems, translating emerging research into scalable, high-quality experiences. Key attributes expected in the role is fluency in algorithm development (prompt optimization and post training), and strong expertise with relevant techniques (reinforcement learning, multimodal reasoning, context compaction - efficiency & memory systems). The role includes the opportunity to partner with world class system engineers to prototype and incorporate bleeding edge algorithmic innovations in the context of emerging agentic experiences. Ability to interface with large scale modeling & data infrastructure is a huge plus.

Minimum Qualifications

• PhD in Electrical Engineering/Computer Science or a related field (mathematics, physics or computer engineering), with a focus on computer vision and/or machine learning or comparable professional experience.
• Strong ML and Generative Modeling fundamentals.
• Hands-on experience in one or more of the following areas: pre-training or post-training of large language models, and reinforcement learning.
• Familiarity with distributed training.
• Proficiency in using ML toolkits, e.g., PyTorch
• Proven track record of research contributions demonstrated through publications in top-tier conferences, or open source contributions to algorithm.

Preferred Qualifications

• Experience with building & deploying Multimodal-LLMs
• Experience building and deploying agentic systems and LLMs with tool-use and memory capabilities

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 $216,200 and $394,000, 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.

Learn about accessibility in Apple's workplace

Learn about reasonable accommodations for job applicants

Apple accepts applications to this posting on an ongoing basis.