Senior ML Researcher: Multimodal LLM Post-Training

Apple, Inc.

Cupertino (CA)

On-site

USD 185,000 - 325,000

Full time

11 hours ago
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Benefits offered by this job

Comprehensive medical and dental cover
Retirement benefits
Discounted products and free services
Tuition reimbursement
Relocation assistance

Job summary

Apple, Inc. in Cupertino, California, is seeking a Senior ML Researcher focused on foundation model post-training, including SFT and RL, to research, design, and deliver models that impact real products.

You will collaborate with research scientists, engineers, and product teams on multimodal use cases such as video understanding, instruction following, and agentic tasks, applying post-training recipes and distillation to advance generative AI while aligning with Apple's human-centered design.

Qualifications

  • MS in CS/ML or related field or equivalent practical experience.
  • 4+ years of research experience in Multi-Modal LLM training and evaluation.
  • Proven track record in multimodal SFT plus distillation / online RL with shipped models or rigorous experiments.
  • Strong programming skills in Python and at least one deep learning framework such as JAX or PyTorch.

Responsibilities

  • Research, design, and deliver models where ML research meets real-world product impact.
  • Collaborate with research scientists, engineers, and product teams to explore new ways generative AI can assist creators.
  • Lead post-training efforts, including formulating hypotheses, data collection, evaluation, and applying SFT and RL techniques.
  • Communicate findings to the broader team and help ship research into Apple's products.

Skills

Python programming
DL frameworks (JAX, PyTorch)

Education

MS in CS/ML or related
PhD in CS/ML or related

Tools

JAX
PyTorch

Job description

Cupertino, California, United States Software and Services

We are looking for a Senior ML Researcher who is passionate about foundation model post-training, including Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL), and has experience with core capabilities such as instruction following, tool use, deep thinking, and reasoning. In this role, you will research, design, and deliver models where machine learning research meets real-world product impact. You will work closely with research scientists, engineers, and product teams to find new ways that generative AI can help our creative users. Your mission is to improve the workflows of millions of creators by combining generative AI with Apple's human-centered design principles.

Description

What makes our work unique is we have many research opportunities in real-world use cases in multimodal space. Our goal is to develop targeted, task-specific capabilities within our models across a broad range of areas, including video understanding, reasoning, instruction following, and agentic tasks. The role involves contributing to every stage of the post-training process: Formulate hypotheses for a use case Define data collection and annotation Build evaluations of model capabilities Apply SFT, advanced reward modeling, RL techniques, and distillation to develop and improve the post-training recipe Execute experiments, validate results, and communicate findings to the broader team If you're passionate about doing research that ships in Apple's legendary products, this is the team for you.

Minimum Qualifications
  • MS in Computer Science, Machine Learning, or a related field, or equivalent practical experience
  • Minimum 4+ years of research experience in Multi-Modal LLM training and evaluation
  • Proven track record in multimodal SFT plus at least one of distillation, preference optimization, or online RL, backed by shipped models or rigorous experiments
  • Strong programming skills in Python and at least one deep learning, framework, such as JAX or PyTorch.
  • Ability to build intuition from a problem statement and translate it into dataset requirements, neural network design, and loss functions.
Preferred Qualifications
  • PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience
  • Experience in GRPO, DPO, Vision-OPD, and visual-token compression
  • Publications in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV)
  • Bonus: Experience in quantization, on-device models and SLM (Small Language Model)

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
  • for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition
  • 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

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