Senior Multimodal LLM Post-Training Researcher

Apple, Inc.; San Diego (CA); On-site; USD 175,000 - 309,000; Full time

Benefits offered by this job

Medical and dental coverage

Employee stock program

Relocation assistance

Tuition reimbursement

Job summary

Apple is seeking a Senior ML Researcher in San Diego to advance foundation model post-training, including supervised fine-tuning and reinforcement learning. You will develop capabilities for instruction following, tool use, and reasoning, delivering models that enhance Apple’s creative user experiences.

You will collaborate with researchers, engineers, and product teams to deploy research into products, define data collection, run experiments, and validate results.

Qualifications

• MS in Computer Science, Machine Learning, or 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 distillation/priority optimization or 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 machine learning research meets real-world product impact
• Work closely with research scientists, engineers, and product teams to apply generative AI to Apple’s products
• Formulate hypotheses, collect data, build evaluations, and improve the post-training recipe

Skills

Python

Multimodal LLM

JAX/PyTorch

Problem to dataset design

Education

MS in Computer Science or related field

Tools

JAX

PyTorch

Job description

Apple is seeking a Senior ML Researcher in San Diego to advance foundation model post-training, including supervised fine-tuning and reinforcement learning. You will develop capabilities for instruction following, tool use, and reasoning, delivering models that enhance Apple’s creative user experiences.

You will collaborate with researchers, engineers, and product teams to deploy research into products, define data collection, run experiments, and validate results.