Senior Multimodal LLM Researcher: Post-Training & RL Lead

Apple Inc.; Seattle (WA); On-site; USD 185,000 - 325,000; Full time

Benefits offered by this job

Employee stock purchase plan

Relocation assistance

Comprehensive medical and dental

Job summary

Apple Inc. is seeking a Senior ML Researcher focused on foundation model post-training, including Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL).

You will explore instruction following, tool use and reasoning to ship real-world capabilities for millions of creators within Apple's human-centered design framework. You will collaborate with research scientists, engineers, and product teams to drive multimodal model capabilities, including video understanding, reasoning, and agentic

Qualifications

• MS in Computer Science, Machine Learning, or related field or equivalent practical experience.
• Minimum 4+ years of research in Multimodal LLM training and evaluation.
• Proven track record in multimodal SFT plus distillation, preference optimization, or online RL.
• Strong Python programming and experience with deep learning frameworks such as JAX or PyTorch.

Responsibilities

• Research, design, and deliver models where ML research meets product impact.
• Collaborate with researchers, engineers, and product teams to apply generative AI for Apple users.
• Contribute to post-training steps including data collection, annotations, and evaluation.
• Execute experiments, validate results, and communicate findings to the team.

Skills

Python programming

JAX or PyTorch

Multimodal LLM

Experiment design & evaluation

Education

MS in Computer Science / ML or related field

PhD (preferred)

Tools

JAX

PyTorch

Job description

Apple Inc. is seeking a Senior ML Researcher focused on foundation model post-training, including Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL).

You will explore instruction following, tool use and reasoning to ship real-world capabilities for millions of creators within Apple's human-centered design framework. You will collaborate with research scientists, engineers, and product teams to drive multimodal model capabilities, including video understanding, reasoning, and agentic