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Parasail

Lead Developer Advocate

Parasail

. Serve as Parasail's technical voice on inference, open weight models, hardware and applications .

Posted 11/6/2026full-timeSan Mateo • California • United StatesSeniorWebsite

Tech Stack

Tools & technologies
Open SourcePython

About the role

Key responsibilities & impact
  • Serve as Parasail's technical voice on inference, open weight models, hardware and applications
  • Conduct original experiments on production inference, including serving engines, hardware, latency, cost and quality
  • Publish technical deep dives and references
  • Share technical work on X, LinkedIn, Hacker News and Parasail's own accounts
  • Write CFPs and give talks at AI engineering, infrastructure and model-building conferences and meetups
  • Run workshops and participate in podcasts and panels
  • Launch new models with open weight labs
  • Demonstrate new silicon capabilities with AMD, Positron and d-Matrix
  • Build integrations with developer frameworks and tools
  • Align with model labs and chip makers on benchmarking and build joint benchmarks
  • Collaborate with performance and platform engineers
  • Represent Parasail with model labs and hardware partners
  • Initially work as an individual contributor, with potential to build and lead a team

Requirements

What you’ll need
  • Technical work in public, such as conference talks and writing that engineers cite, from developer advocacy, ML education, research or engineering
  • Build with LLMs in Python
  • Ability to read serving engine code
  • Ability to explain GPU-level tradeoffs behind latency, throughput and cost
  • Ability to communicate complex systems ideas clearly on stage and in writing
  • Contributions to or maintenance of open source used by developers
  • Knowledge of people across the AI ecosystem, or ability to meet them quickly
  • Comfortable building a function without an existing playbook
  • Nice to have: experience with vLLM or SGLang, or accelerators beyond NVIDIA
  • Nice to have: published evaluations or benchmark methodology for LLM systems
  • Nice to have: accepted talks at major AI, ML or systems conferences
  • Nice to have: a following on X, LinkedIn or elsewhere earned through technical work
  • Nice to have: research or teaching background in ML or systems

Benefits

Comp & perks
  • Meaningful equity
  • Comprehensive health, dental and vision coverage
  • Generous PTO and company holidays
  • 401(k)
  • Family planning (fertility) benefits
  • Reasonable accommodation for applicants with physical and mental disabilities