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Senior ML Researcher: Multimodal LLM Post-Training

Apple· Software and Services
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Hybrid (San Diego, CA), Hybrid (Cupertino, CA), Hybrid (Seattle, WA)$175k - $308.5kfull-timePosted 1w ago

About the role

Senior ML Researcher focused on foundation model post-training (SFT and RL) with multimodal capabilities. Collaborates with research scientists, engineers, and product teams to develop task-specific, real-world solutions for generative AI that enhance creators' workflows while aligning with Apple’s human-centered design.

Responsibilities

  • 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
  • Research, design, and deliver models with real-world product impact
  • Work with cross-functional teams to apply multimodal models to video understanding, reasoning, instruction following, and agentic tasks

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 (e.g., JAX or PyTorch)
  • Ability to translate problem statements into dataset requirements, neural network design, and loss functions
  • 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)

Skills

Required:Post-training methodologies (SFT, RL, distillation)Multimodal LLMsPython programmingDeep learning frameworks

Benefits

  • Comprehensive medical and dental coverage
  • Retirement benefits
  • Discounted products and free services
  • Educational expense reimbursement (tuition)
  • Discretionary bonuses or commission potential
  • Relocation assistance
  • Apple employee stock programs optional participation
  • Stock purchase plan
  • EEO inclusion and diversity commitments
Last updated Oct 16, 2026. Interested? Apply on the company site.

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