Drimva

RadixArk

Member of Technical Staff — Product

$200K–$400K

Palo Alto +1 · On-site · Staff · Full-time · Posted May 7, 2026

Location
Palo Alto
San Francisco
Experience
5+ years of software engineering experience building production systems, OR 3+ years with a PhD in a relevant field.
Education
Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.

About the job

Build and lead developer-facing products that make RadixArk’s inference and training infrastructure accessible through APIs, SDKs, dashboards, and other tools.

What you'll do

  • Design, ship, and maintain developer-facing product experiences, including APIs, SDKs, CLIs, dashboards, and playgrounds.
  • Own product engineering work end to end, from design through launch, monitoring, and iteration; address performance, reliability, and scalability.
  • Partner with product, research, infrastructure, and users to prioritize work, improve experiences, and guide technical direction.

What they ask for

  • Bachelor’s degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience.
  • 5+ years of software engineering experience building production systems, OR 3+ years with a PhD in a relevant field.
  • Strong programming skills in at least one of: Python, TypeScript/JavaScript, Go, C++, or Rust.
  • Experience shipping developer-facing or product-facing software end to end, and using data and analysis to inform technical and design decisions.

Nice to have

  • Experience building products on AI/ML infrastructure, model serving, or large-scale distributed systems.
  • Experience with open source, developer experiences, or integrating AI tools into engineering workflows.

Pay

$200,000 - $400,000 USD annual base salary

Tools

Python, TypeScript/JavaScript, Go, C++, Rust, SGLang, Miles, vLLM

AI focus

Build developer-facing products for AI inference and training infrastructure; preferred experience includes AI/ML infrastructure and integrating AI tools into engineering workflows.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 6, 2026 (UTC)