Member of Technical Staff - Recommendation Systems

xai· Engineering
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📍 Palo Alto, CA

About this role

ABOUT xAI

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.

ABOUT THE ROLE:

We’re seeking exceptional Applied engineers to join a high-priority project that approximately 600 million monthly users use. This is an exciting opportunity for individuals with a engineer or scientist background to apply their skills to recommendation systems, ranking algorithms, search technologies, and many other systems. You’ll work at the intersection of advanced AI development and real-world impact, enhancing the ability to connect users with relevant content, accounts, and experiences.

RESPONSIBILITIES:

  • Designing and architecting recommendation algorithms across various product surfaces
  • Leverage all of xAI’s infra and AI stacks to dramatically enhance the user experience
  • Write data pipelines and training jobs that continuously learn from product data.
  • Iterate and improve the algorithm by gathering user feedback in real time through experimentation
  • Ensuring scalability and efficiency of machine learning systems

BASIC QUALIFICATIONS:

  • Knowledge of data infrastructure like Kafka, Clickhouse, and Spark
  • Experienced in implementing recommender systems and/or deep learning applications at industrial scale
  • Skilled in one or more DL software frameworks such as JAX or PyTorch
  • Exceptional candidates may be experienced in writing CUDA kernels

COMPENSATION AND BENEFITS:

$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.

xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

Frequently Asked Questions

Is the salary disclosed for the Member of Technical Staff - Recommendation Systems position at xai?
The salary for this Member of Technical Staff - Recommendation Systems role at xai is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Member of Technical Staff - Recommendation Systems position at xai located?
This Member of Technical Staff - Recommendation Systems role at xai is based in Palo Alto, CA. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Which team or department does the Member of Technical Staff - Recommendation Systems at xai belong to?
This Member of Technical Staff - Recommendation Systems position is part of the Engineering department at xai. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Member of Technical Staff - Recommendation Systems position at xai?
Click the "Apply Now" button on this page. You will be redirected to xai's official application portal hosted on greenhouse where you can submit your application directly.
When was the Member of Technical Staff - Recommendation Systems job at xai posted?
This Member of Technical Staff - Recommendation Systems position at xai was posted on Apr 10, 2025. Apply as soon as possible — early applications are often reviewed first.
Member of Technical Staff - Recommendation Systems
xai
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