Member of Technical Staff - Reasoning Numerics / Quantization
Job Description
- PhD with AI or other scientific domains.
- Strong knowledge in quantization and numerics in LLM inference and training.
- Experience in building testing / tools to analyze numerics.
- Broad understanding of training/inference frameworks and reinforcement learning techniques.
- Develop low-precision solutions, from kernel to algorithm, to enhance efficiency in RL training and inference of flagship models.
- Analyze numerical properties of flagship models and their training dynamics, and develop tools to enhance and monitor numerical stability.
- Co-design models, systems, and recipes for numerically stable and optimal training and inference.
- Equity
- Comprehensive medical, vision, and dental coverage
- Access to a 401(k) retirement plan
- Short & long-term disability insurance
- Life insurance
- Various other discounts and perks
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 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 RL infra team builds an internal RL framework to enable large scale reasoning training to build next state of art flagship models. You will be an expert in numerics / low-precision training and inference to enable efficient and stable RL training.
Focus
- Develop low-precision solutions, from kernel to algorithm, to enhance efficiency in RL training and inference of flagship models.
- Analyze numerical properties of flagship models and their training dynamics, and develop tools to enhance and monitor numerical stability.
- Co-design models, systems, and recipes for numerically stable and optimal training and inference.
Exceptional candidates may have:
- PhD with AI or other scientific domains
- Strong knowledge in quantization and numerics in LLM inference and training
- Experience in building testing / tools to analyze numerics
- Broad understanding of training/inference frameworks and reinforcement learning techniques
Tech Stack
- Python / Rust / C++ / CUDA
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:
1. Coding assessment in a language of your choice.
2. Two systems hands-on: Demonstrate practical skills in live problem-solving sessions that involve both system design and coding.
3. 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.
Location
- We hire engineers 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.
Annual Salary Range
$180,000 - $440,000 USD
Benefits
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.
