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xAI’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.
The Starfleet team is responsible for creating the tools and systems necessary to drive frontier model performance. We collaborate closely with our research teams and AI tutor teams to develop new solutions that accelerate research progress across model capabilities, evaluation, safety, and alignment.
About the RoleIn this role you might:
- Design and build robust, scalable backend systems to power our AI-driven tools and platforms.
- Develop APIs and distributed systems that handle high-throughput data processing for model training and evaluation.
- Create secure, reliable pipelines to support innovative human data generation and agentic workflows.
- Optimize infrastructure to leverage cutting-edge GPU resources for maximum performance.
- Innovate new approaches that bring us closer to our goal: to develop AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.
Exceptional candidates may have:
- Experience building high-performance backend systems in dynamic, fast-paced environments - as a tech lead, former founder, etc.
- Expertise in designing scalable distributed systems and APIs with a compiled language like Rust or C++.
- Experience optimizing data pipelines for machine learning workloads or real-time applications.
- Familiarity with frontend technologies (e.g., TypeScript, React) to collaborate seamlessly with cross-functional teams.
- Typescript, Python, Rust
- React, Express, PostgreSQL
The role is based in the Bay Area [San Francisco and Palo Alto]. Candidates are expected to be located near the Bay Area or open to relocation.
Interview ProcessAfter submitting your application, the team reviews your CV and statement of exceptional work. If your application passes this stage, you will be invited to a 15-minute interview (“phone interview”) during which a member of our team will ask some basic questions. If you clear the initial phone interview, you will enter the main process, which consists of four technical interviews:
- Coding assessment in a language of your choice.
- Front end technical interview, in React/Typescript
- Systems hands-on: Demonstrate practical skills in a live problem-solving session.
- Meet the Team: Present your past exceptional work and your vision with xAI to a small audience.
Our goal is to finish the main process within one week. All interviews will be conducted via Google Meet.
Annual Salary Range$180,000 - $440,000 USD
BenefitsBase 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 & long-term disability insurance, life insurance, and various other discounts and perks.
xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.
xAI San Francisco, California, USA Office
3180 18th St., San Francisco, CA, United States
xAI Palo Alto, California, USA Office
1450 Page Mill Road, Palo Alto, CA, United States
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
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- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
