Principal Research Scientist – Scaling

What you'll do

• Lead research programs and large-scale experiments on foundation model efficiency, optimization, adaptation, and scaling.
• Collaborate with systems, infrastructure, product, and engineering teams to improve distributed training and inference and bring research into production.
• Mentor researchers and engineers, establish research practices, and represent the work through publications, talks, and collaborations.

What they ask for

• Proven ability to lead a research team developing novel foundation-model efficiency techniques, with industry impact.
• Deep expertise in at least one of generative AI, LLMs, distributed ML systems, model optimization, or responsible AI, emphasizing scaling and efficiency.
• Strong programming skills and demonstrated ability to write high-quality, efficient code in Python and PyTorch.
• Ability to translate research into scalable product capabilities and influence cross-functional roadmaps; strong communication and leadership skills.

Nice to have

• Experience at the intersection of systems and ML, such as distributed training frameworks, compiler or kernel optimization, or efficient model design.
• Strong industry or academic network and research impact, such as top-conference publications, open-source contributions, or widely used systems.

Pay

$280,000 — $350,000 USD (base salary)

Tools

Python, PyTorch, ICLR, ICML, NeurIPS, MLSys

AI focus

Leads research on LLM and foundation-model scaling, post-training, reinforcement learning, optimization, training and inference efficiency, and responsible deployment.