xAI
Full TimeDesign and optimize inference systems for reinforcement learning workloads ranging from small ablations to production scale. You'll analyze performance bottlenecks in large-scale RL systems and implement novel RL techniques with the modeling team. The role requires experience building and optimizing distributed systems, LLM inference, and proficiency in Python, C++, or Rust with PyTorch, JAX, or CUDA. Base salary $180,000–$440,000 USD plus equity and benefits.
Written from this posting by Neural Jobs AI. The full description is below.
SpaceXAI’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.
The RL infrastructure team is looking for an engineer to help with low precision RL training and inference.
RESPONSIBILITIES:
$180,000 - $440,000 USD
Base salary is just one part of our total rewards package at SpaceXAI, 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.
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xAI develops Grok, a family of large language models, and builds the large-scale training and inference infrastructure behind them, including the Colossus supercomputing cluster.
Founded in 2023, the company focuses on frontier model research and deployment across the X platform and its own products.
United States
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