Senior ML Researcher: Multimodal LLM Post-Training

What you'll do

• Formulate use-case hypotheses; define data collection and annotation; and build capability evaluations.
• Apply SFT, reward modeling, RL, and distillation to develop and improve post-training recipes.
• Run experiments, validate results, and communicate findings to the team.

What they ask for

• 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.
• Track record in multimodal SFT plus at least one of distillation, preference optimization, or online RL, supported by shipped models or rigorous experiments.
• Strong programming skills in Python and at least one deep learning framework, such as JAX or PyTorch.

Nice to have

• Experience in GRPO, DPO, Vision-OPD, and visual-token compression.
• Publications in top-tier ML conferences; experience in quantization, on-device models, and SLM is a bonus.

Pay

$175,000 to $308,500 USD base salary; $184,700 to $324,800 USD base salary

Tools

Python, JAX, PyTorch, GRPO, DPO, Vision-OPD

AI focus

Multimodal LLM post-training, including SFT, reward modeling, RL, and distillation, for video understanding, reasoning, instruction following, and agentic tasks.