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 engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
About the Team
The AI search team aims to make Grok the best AI system for research, information retrieval and gathering real-time information from various sources. The team is responsible for curating high quality data and hard problems for RL training, making evaluations to benchmark AI systems and capture product issues, and building tools to unleash the capabilities of reasoning models.
About the Role
In this role you might:
- Build evaluation benchmarks to the next generation of search/research agents.
- Innovate and curate challenging RL data with scalable synthetic/human data pipeline
- Innovate data, verification and RL algorithms to build the best open-ended research system.
- Build various tools to help model exploring seamlessly on the internet.
Exceptional candidates may have:
- Experience with LLM and information retrieval evaluation data curation
- Experiences with human/synthetic data generation for RL
- Experience with AI search or Agentic search systems
- Strong engineering abilities
Location
- The role is based in Palo Alto. Our team usually works from the office 5 days a week but allow work-from-home days when required. Candidates are expected to be located near Palo Alto or open to relocation.
Interview Process
After 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.
- Researcher technical sessions (2): These sessions will be testing your ability to formulate, design and solve concrete problems in real world with LLM. It can be research or engineering, depending on background/experience.
- 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
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 & long-term disability insurance, life insurance, and various other discounts and perks.
Interested in building your career at xAI? Get future opportunities sent straight to your email.
Apply for this job
*
indicates a required field
First Name *
Last Name *
Email *
Phone *
Resume/CV *
Enter manually
Accepted file types: pdf, doc, docx, txt, rtf
What exceptional work have you done? *
In 100 words or less, tell us about a piece of work you are most proud of.
Will you now, or in the future, require sponsorship for employment visa status (e.g., H-1B visa) to legally work for X.AI LLC in the U.S.? * Select...
Current company
If you are currently employed in the field, please tell us the name of your employer.
If you are currently employed in the field, please tell us your role including your seniority level (e.g. Software Engineer II).
LinkedIn Profile
If you have a public LinkedIn profile, please provide its URL.
X Profile
If you have a public X profile, please provide its URL.
If you have a Google Scholar page, please provide its URL.
#J-18808-Ljbffr