# Member of Technical Staff - Evaluation Infrastructure

**Company**: SpaceXAI
**Location**: Palo Alto, CA
**Experience**: senior
**Job type**: full-time
**Salary**: $180,000 - $440,000 USD
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/xai/jobs/5252714007?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_a4fded1a-c17

## Description

SpaceXAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.

The RL infrastructure team is looking for an engineer to help develop evaluation infrastructure.

### Responsibilities

- Build highly reliable, efficient, and easy-to-use infrastructure that runs all evaluations at scale.

- Collaborate closely with modeling and evaluation teams on developing new evaluations, maintaining evaluation signal quality, and building internal tooling to support training the next generation of models.

- Identify and resolve performance bottlenecks in all layers of the evaluation infrastructure stack, including inference, capacity fleet management, asynchronous evaluation orchestration, and more.

### Basic Qualifications

- Experience in building, debugging, and optimizing the 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 evaluations.

### 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 and long-term disability insurance, life insurance, and various other discounts and perks.

## Skills

### Required
- large-scale distributed systems
- debugging
- optimizing efficiency

### Nice to have
- LLM inference
- GPU compute management
- workload scheduling
- dynamic resource optimization
- developing interfaces for comparing models and evaluations

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/xai/jobs/5252714007?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)