ML Infrastructure Engineer

Strativ Group; Menlo Park (CA); On-site; USD 250,000 - 320,000; Full time

Job summary

A leading AI lab in Menlo Park is seeking a Staff Infrastructure Engineer to architect and build the compute substrate for next-generation AI systems. The ideal candidate has 5+ years in Software / ML Infrastructure Engineering, with deep experience in distributed systems and GPU orchestration. Join a team pushing the boundaries of real-time generative models with a focus on low-latency performance and scalability.

Qualifications

• 5+ years of experience in Software / ML Infrastructure Engineering.
• Deep experience with distributed systems and GPU orchestration for high‑performance ML workloads.
• Proficiency in Python, Go, or similar, and strong grasp of software engineering best practices.
• Hands‑on expertise with Kubernetes, Docker, and IaC (Terraform).
• Experience optimizing model serving and data pipelines for latency and scalability.

Responsibilities

• Work directly with founders to architect and build the compute substrate.
• Design and optimize the inference platform and GPU-based training clusters.
• Play a key role in scaling systems for research and production.

Skills

Distributed systems

GPU orchestration

Python

Go

Kubernetes

Docker

Infrastructure as Code (Terraform)

Job description

Staff Infrastructure Engineer

We are partnered with a Stealth AI Lab (backed by top-tier investors and advised by pioneering figures in generative and interactive media) that is hiring a Staff Infrastructure Engineer. The company pushes the boundaries of real-time generative models, building the core infrastructure that enables next‑generation video AI. Their work sits at the intersection of generative media, simulation, and multimodal interaction, redefining how humans and AI co‑create across gaming, film, education, and immersive content.

As a Staff Infra Engineer, you will work directly with the founders to architect, build, and scale the compute substrate that powers this next generation of AI. You’ll design and optimize the inference platform, GPU‑based training clusters, and data processing pipelines that drive real‑time creativity and discovery. You’ll play a key role in scaling systems for both research and production—ensuring low‑latency performance, high availability, and efficient utilization across petabyte‑scale data and model‑serving workloads.

Pay Range

$250,000.00/yr - $320,000.00/yr

Key Experience Required

• 5+ years of experience in Software / ML Infrastructure Engineering.
• Deep experience with distributed systems and GPU orchestration for high‑performance ML workloads.
• Proficiency in Python, Go, or similar, and strong grasp of software engineering best practices.
• Hands‑on expertise with Kubernetes, Docker, and IaC (Terraform).
• Experience optimizing model serving and data pipelines for latency and scalability.
• A builder’s mindset — you thrive in ambiguity, pick the right tools for the job, and ship.

Seniority level: Mid‑Senior level. Employment type: Full‑time. Job function: Information Technology.

This is a chance to join a team working at the frontier of real‑time AI systems — please apply ASAP for more info.