Infrastructure Engineer - Post-training
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 and researchers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
About the Role
The post-training team at xAI transforms powerful pre-trained models to become steerable, versatile, and capable of understanding and addressing real-world challenges.
To accomplish this, we are looking for experienced AI infrastructure engineers to develop and optimize frameworks tailored for large-scale machine learning tasks, particularly in the areas of reinforcement learning and agent systems.
The role involves building high-performance and scalable software to support cutting-edge AI research, employing advanced technologies to expand the limits of what AI can achieve with increased data and computational resources.
Focus
- Building efficient and user-friendly training and evaluation frameworks for model fine-tuning and reinforcement learning.
- Building efficient and user-friendly software frameworks for large-scale agent simulation and execution.
- Building flexible and performant bulking inference framework to enable synthetic data generation and model-based data improvement research.
Ideal Experiences
- Expert in developing software for large-scale distributed machine learning systems (e.g. language modeling training and reinforcement learning).
- Expert in GPUs, Kubernetes, and JAX (or PyTorch).
- Experienced in standard software engineering best practices (CI/CD) and care about code quality, testing, and performance.
Location
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.
Tech Stack
- Python
- JAX
- Rust
- CUDA & NCCL
Interview Process
After submitting your application, the team will review 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 programming language of your choice.
- 2 x post-training infra technical sessions: These sessions will be assessing your engineering skills to design and implement solutions to solve infra problems in post-training.
- 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
xAI is an equal opportunity employer and does not unlawfully discriminate based on race, color, religion, ethnicity, ancestry, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, disability, medical conditions, genetic information, marital status, military or veteran status, or any other applicable legally protected characteristics.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all applicable federal, state, and local laws, including the San Francisco Fair Chance Ordinance, Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
For Los Angeles County (unincorporated) Candidates:
xAI reasonably believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of a conditional offer of employment:
- Access to information technology systems and confidential information, including proprietary and trade secret information, and/or user data;
- Interacting with internal and/or external clients and colleagues; and
- Exercising sound judgment.