Member of Technical Staff - RL Infrastructure

<div class="content-intro"><h3><strong><span style="font-family: arial, helvetica, sans-serif;">About xAI</span></strong></h3> <p><span style="font-family: arial, helvetica, sans-serif;">xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. </span><span style="font-family: arial, helvetica, sans-serif;">Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. </span><span style="font-family: arial, helvetica, sans-serif;">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. </span><span style="font-family: arial, helvetica, sans-serif;">All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.</span></p></div><h3>ABOUT THE ROLE:</h3> <p>xAI is seeking experienced software engineers to create robust data pipelines, comprehensive evaluations for benchmarking LLMs, and automation frameworks to increase the productivity of researchers and engineers.</p> <p>Typical problems you will deal with include the following:</p> <ol> <li>We have a new agentic model capability that we’d like to improve. How do we design an efficient and robust environment for the agent to perform actions in?</li> <li>Evaluations and observability are a core part of knowing what we need to improve in our models. What new features can we add into our evaluation framework to ease the workflow of researchers &amp; engineers and increase observability?</li> <li>A new open-source evaluation dataset has been released and researchers would like to track our models performance on it. How should we onboard it into our internal evaluation framework?</li> <li>Datasets have been collected that require complex pre-processing to prepare it for large-scale RL training. How do we standardize our preprocessing pipelines to minimize dataset onboarding time?</li> <li>A researcher on the team has an idea for how to augment a dataset to produce additional training data. How should we go about creating the data augmentation pipeline?</li> </ol> <h3>RESPONSIBILITIES:</h3> <ul> <li>Creating and maintaining frameworks for agent, data, and model evaluation tasks.</li> <li>Building environments for AI agents.</li> <li>Tools for automating common workflows.</li> <li>Improving alerts, metrics and error handling on large scale RL jobs.</li> <li>Refactoring existing agent, data, eval, training frameworks for better modularity.</li> <li>Designing operation procedures and coding standards to streamline the transition from small scale experimentation to large scale RL training.&nbsp;</li> <li>Writing unit tests, CI/CD frameworks to support rapid development cycles.</li> </ul> <h3>BASIC QUALIFICATIONS:</h3> <ul> <li>Experience building and maintaining frameworks that are used by many engineers.</li> <li>Experience in building high-performance sandboxes, virtual machines, and simulations.</li> <li>Experience building full-stack apps for automating workflows and data visualization.</li> <li>Experience in rapid iteration of research to production cycles.</li> <li>Experience in test automation, CI/CD.</li> </ul> <h3><strong>COMPENSATION AND BENEFITS:</strong></h3> <p>$180,000 - $440,000 USD</p> <p>Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short &amp; long-term disability insurance, life insurance, and various other discounts and perks.</p><div class="content-conclusion"><p><em>xAI is an equal opportunity employer. For details on data processing, view our&nbsp;</em><em><a href="https://x.ai/legal/recruitment-privacy-notice" target="_blank">Recruitment Privacy Notice</a>.</em></p></div>