M
$150,000 – $350,000
Listed on Modal’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Modal is hiring a researcher to drive inference optimization for their AI infrastructure platform, focusing on techniques like speculative decoding and quantization that reduce cost-per-token and latency for production LLM workloads. This role suits someone with a background in LLM systems who can own research projects end-to-end, collaborate with customers and external labs, and ship work that becomes part of Modal's serving stack.
Our summary, not Modal’s wording. The full posting is on their site.
Skills this role names
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What they ask for
Required
- Research or systems background in LLM inference with demonstrable work
- Fluency across LLM serving stack from kernels to schedulers
- Track record of shipping research or systems used by others
- Ability to independently drive research projects from conception to results
- In-person work in NYC or San Francisco office