Member of Technical Staff - Evaluation Infrastructure

Xai

Palo Alto, CA

Who this role is best for

A natural match if you have experience in distributed systems and LLM inference.

Best fit for

Candidates with distributed systems expertise and interest in AI evaluation frameworks
— “Experience in building, debugging, and optimizing efficiency of large-scale distributed systems”
Individuals who thrive in small, flat teams and take initiative in problem-solving
— “Leadership is given to those who show initiative and consistently deliver excellence”
Engineers with a background in GPU compute and workload scheduling
— “Experience in GPU compute management, workload scheduling, and dynamic resource optimization”

Things to consider

The role demands direct, hands-on contributions to the company's mission
— “All employees are expected to be hands-on and to contribute directly to the company’s mission”
Strong communication skills are a non-negotiable requirement
— “All employees are expected to have strong communication skills”

How to stand out

Highlight experience in asynchronous orchestration and performance optimization
— “Identify and resolve performance bottlenecks in all layers of the eval infrastructure stack”
Showcase your ability to build and maintain internal tooling for model training
— “Collaborate closely with modeling & evaluation teams on developing new evals, maintaining evaluation signal quality, and building internal tooling to support training our next-generation of models”

Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

developed highly reliable, efficient, and easy to use infrastructure
collaborated closely with modeling & evaluation teams
identified and resolved performance bottlenecks

Typical background

experience in building, debugging, and optimizing efficiency of large-scale distributed systems

Skills & requirements

Required

Large-scale Distributed SystemsBuilding And Debugging InfrastructureOptimizing Efficiency Of Systems

Preferred

LLM InferenceGPU Compute ManagementWorkload SchedulingDynamic Resource OptimizationDeveloping Interfaces For Comparing Models And Evals

Stack & domain

BuildingDebuggingOptimizing EfficiencyLarge-scale Distributed SystemsLLM InferenceGPU Compute ManagementWorkload SchedulingDynamic Resource OptimizationDeveloping InterfacesComparing ModelsEvalsCommunicationAIEngineering

About the role

Original posting from Xai via Greenhouse

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
ABOUT THE ROLE:
The RL infrastructure team is looking for an engineer to help develop our evaluation infrastructure.
RESPONSIBILITIES:
Build highly reliable, efficient, and easy to use infrastructure that runs all our evaluations at scale
Collaborate closely with modeling & evaluation teams on developing new evals, maintaining evaluation signal quality, and building internal tooling to support training our next-generation of models
Identify and resolve performance bottlenecks in all layers of the eval infrastructure stack, including inference, capacity fleet management, asynchronous eval orchestration, and more
BASIC QUALIFICATIONS:
Experience in building, debugging, and optimizing efficiency of large-scale distributed systems
Willingness to dive deep and solve hard problems at all levels of the stack
PREFERRED SKILLS AND EXPERIENCE:
Experience in LLM inference
Experience in GPU compute management, workload scheduling, and dynamic resource optimization
Experience in developing interfaces for comparing models and evals
COMPENSATION AND BENEFITS:
$180,000 - $440,000 USD
Base salary is just one part of our total rewards package at SpaceXAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.
SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

Source: Xai careers (Greenhouse)