Kuzco
AI

Senior ML infrastructure engineer

Kuzco · San Francisco, CA, USA · $180k - $250k

Actively hiring Posted over 1 year ago
Kuzco is seeking a Senior ML Infrastructure Engineer to join our team. This role involves developing large-scale, fault-tolerant systems that handle millions of large language model inference requests per day. If you are passionate about developing next-generation ML systems that operate at scale, we want to hear from you.

About Kuzco

We are building a distributed LLM inference network that combines idle GPU capacity from around the world into a single cohesive plane of compute that can be used for running large-language models like Llama and Mistral. At any given moment, we have over 5,000 GPUs and hundreds of terabytes of VRAM connected to the network. Learn more here.

We are a small, well-funded team of staff-level engineers who work in-person in downtown San Francisco on difficult, high-impact engineering problems. Everyone on the team has been writing code for over 10 years, and has founded and run their own software companies. We are high-agency, adaptable, and collaborative. We value creativity alongside technical prowess and humility. We work hard, and deeply enjoy the work that we do; we are almost always online at least six days per week.

About The Role

You will be responsible for designing and implementing the core systems that power our globally distributed LLM inference network. You'll work on problems at the intersection of distributed systems, machine learning, and resource optimization.

Key Responsibilities

  • Design and implement scalable distributed systems for our inference network
  • Develop models for efficient resource allocation across a network of heterogeneous hardware and quickly changing topology
  • Optimize network latency, throughput, and availability
  • Build robust logging and metrics systems to monitor network health and performance
  • Conduct reviews of architecture and system design to ensure use of best practices
  • Collaborate with founders, engineers, and other stakeholders to improve our infrastructure and product offerings


What We're Looking For

  • Very strong problem-solving skills and ability to work in a startup environment
  • 5+ years of experience in building high performance systems
  • Strong programming skills in Typescript, Python, and one of Go, Rust, or C++
  • Solid understanding of distributed systems concepts
  • Knowledge of orchestrators and schedulers like Kubernetes and Nomad
  • Use of AI tooling in development workflow (ChatGPT, Claude, Cursor, etc)
  • Experience with LLM inference engines like vLLM or TensorRT-LLM is plus
  • Experience with GPU programming and optimization (CUDA experience is a plus)


Compensation

We offer competitive compensation, equity in a high-growth startup, and comprehensive benefits. The base salary range for this role is $180,000 - $250,000, plus equity and benefits, depending on experience.

Equal Opportunity

Kuzco is an equal opportunity employer. We welcome applicants from all backgrounds and don't discriminate based on race, color, religion, gender, sexual orientation, national origin, genetics, disability, age, or veteran status.

If you're excited about building the future of developer-first AI infrastructure, we'd love to hear from you. Please send your resume, LinkedIn, and GitHub to [email protected].

Tags & focus areas

Used for matching and alerts on DevFound
Infrastructure Engineer Machine Learning Ai Senior Kubernetes Rust Typescript Solana Python
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.