Senior Multimodal LLM Post-Training Researcher

Apple Inc.; Cupertino (CA); Hybrid; USD 195,000 - 325,000; Full time

Benefits offered by this job

Comprehensive medical and dental cover

Retirement benefits

Discounted products and free services

Tuition reimbursement / education"

Relocation assistance

Job summary

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

You will research, design, and deliver models with real-world product impact, collaborating with researchers, engineers, and product teams to enhance creative workflows through generative AI and human-centered design. Our work spans real-world multimodal use cases like video understanding and instruction following.

Qualifications

• MS in Computer Science, Machine Learning, or related field or equivalent practical experience.
• Minimum 4+ years of research in multi-modal LLM training and evaluation.
• Proven track record in multimodal SFT plus distillation, preference optimization, or online RL with shipped models or rigorous experiments.
• Strong programming skills in Python and at least one deep learning framework such as PyTorch or JAX.

Responsibilities

• Formulate hypotheses for a use case and define data collection requirements.
• Build evaluations of model capabilities and measure outcomes.
• Apply SFT, reward modeling, RL techniques, and distillation to post-training recipes.
• Execute experiments, validate results, and communicate findings to the team.

Skills

Python programming

Multimodal ML

Research experience

Education

MS in Computer Science or related field

PhD (preferred) in ML/CS

Tools

PyTorch

JAX

Job description

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

You will research, design, and deliver models with real-world product impact, collaborating with researchers, engineers, and product teams to enhance creative workflows through generative AI and human-centered design. Our work spans real-world multimodal use cases like video understanding and instruction following.