Job Description

AI Researcher

$200,000- $300,000 + Equity

Onsite – San Francisco

We’re partnering with a well-funded, deeply technical startup at the intersection of systems infrastructure and advanced AI. Founded by experts from top research institutions and industry-leading companies, the team is tackling foundational questions in model efficiency and infrastructure optimization.

They’re currently looking for an AI Researcher with a strong background in deep learning and systems-level thinking. This role is ideal for someone who’s less focused on application-layer AI and more interested in how models run under the hood — including infrastructure efficiency, LLM internals, and GPU-level optimization.

In this role, you’ll explore:

• How AI workloads run on modern infrastructure
• Techniques for improving inference speed, model efficiency, and scalability
• Low-level LLM internals, memory bottlenecks, and system optimization strategies
• Deep learning systems research, potentially leading to publications and open-source contributions

Preferred background:

• Deep understanding of large-scale model training and inference
• Experience with LLMs, inference runtimes, and GPU optimization
• Curiosity for how models operate across stacks — from token to transistor

This is a highly collaborative, research-forward environment. The team works onsite in San Francisco five days a week, with flexibility around hours as needed. It’s a tight-knit group of researchers and engineers building toward long-term technical breakthroughs.

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