Senior Engineer, xAI
Post-Training Infrastructure
Building artificial intelligence
Open for applications
Building artificial intelligence
1001+ employees
Open for applications
1001+ employees
Company mission
To build AI systems that can help humanity understand the world better.
Role
Who you are
- 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
- Built scalable training framework for AI models in HPC clusters, including but not limited to
- Scalable orchestration framework and tools
- Reinforcement learning framework consists of asynchronous training, inference, simulation and more components
- Experience in configuring and troubleshooting operating systems for maximum performance
- Experience in building high-performance sandboxes, virtual machines and simulations
What the job involves
- 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
- XAI is seeking experienced software engineers to design, implement and optimize large-scale distributed training systems for LLM, particularly in the areas of Reinforcement Learning (RL) and Agent
- The training system needs to be robust, fast, and reasonably flexible to support state-of-the-art research
- Design and implement distributed RL training systems
- Profile, debug and optimize system performance
- Software and algorithm co-design with researchers
- Typical problems you will deal with:
- We have a new algorithm that requires a certain computation / communication pattern that the current system does not support or is very inefficient to handle. How should we refactor or improve the current system to support this algorithm?
- We have a new pre-training model, which has very different traits compared to the previous generation. As a result, the current system does not quite work. How should we refactor or improve the current system?
- The amount of FLOPs / HBM bandwidth / throughput the current system can achieve is only “XXX”, which is only “YY%” of the theoretical limit. How much can we improve?
- The training run restarts / crashes every “XXX” hours. What are the root causes of these restarts / crashes? Is there any way to reduce the errors?
Application 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 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
- Two systems hands-on: Demonstrate practical skills in live problem-solving sessions that involve both system design and coding
- 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. We don’t rely on recruiters for assessments. Every application is reviewed by a member of our technical team. All interviews will be conducted via Google Meet
Our take
xAI is Elon Musk's venture into the world of artificial intelligence, and like all things Musk, it's going big. Its setting out to build AI that helps humanity understand the universe and its starting with Grok, its conversational AI chatbot already integrated into X (formerly Twitter). With access to real-time data and a powerful ecosystem of Musk-led companies, xAI is certainly pushing towards artificial general intelligence at serious scale.
Like all bold ventures, xAI has faced its share of controversy, from questions about regulation to the overlap across Musk's businesses. But fans are still seeing the bigger picture: an interconnected tech ecosystem where AI, social media, and space exploration feed into one another.
Recently, the company made headlines with its massive "Colossus" supercomputer project, powered by tens of thousands of Nvidia GPUs. While the data center's temporary power setup has faced environmental scrutiny, the scale of ambition is certainly undeniable. From launching tap-to-pay features on X to building one of the most powerful AI training systems on Earth, xAI is moving fast.
Steph
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 3 rounds)
Dec 2024
$6bn
SERIES C
May 2024
$6bn
SERIES B
Total funding: $12.1bn
Company benefits
- Health and wellness: Comprehensive health insurance including medical, dental, vision, and disability coverage
- Life and family: Life and AD&D insurance and fertility benefits to ensure our team’s well-being and peace of mind
- Flexible vacation: We work hard but avoid burn out. Take time off when you need it
- Visa sponsorship: We support international talent with visa sponsorship to join our team
- 401(k) plan: Retirement savings plan to secure your financial future
Company HQ
Downtown, Burlingame, CA
Leadership
Elon Musk
(Founder)Founder, Chairman, CEO, and CTO of SpaceX. CEO and Product Architect of Tesla. Chairman and CTO of X Corp, founder of the Boring Company, co-founder of Neuralink and OpenAI, and president of the Musk Foundation.
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