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AI Engineer & Researcher - Reasoning Post-training

Salary

$180k - $440k

Min Experience

3 years

Location

Palo Alto, CA

JobType

full-time

About the job

Info This job is sourced from a job board

About the role

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. As an AI Engineer & Researcher - Reasoning Post-training at xAI, you will drive the evolution of our AI models' reasoning capabilities through inventive post-training approaches, embracing a broad scope that spans from conceptual exploration to practical implementation. This role demands a blend of technical depth and boundless creativity, where you'll refine pre-trained models to excel in logical inference, multi-step problem-solving, and adaptive thinking—without delving into initial training phases. By devising unconventional techniques and fostering creative breakthroughs, you'll help our AI systems tackle complex, real-world challenges with unprecedented intelligence and reliability, collaborating across teams to turn bold ideas into transformative enhancements. Focus: Post-Training Optimization: Apply and innovate on post-training methods like fine-tuning, reinforcement learning variants, or data augmentation to sharpen reasoning skills, ensuring models deliver more accurate, coherent, and insightful outputs. Creative Methodology Design: Invent novel strategies for enhancing reasoning, such as custom prompting frameworks, synthetic reasoning datasets, or hybrid techniques that push the limits of model cognition through out-of-the-box thinking. Problem-Solving Exploration: Tackle broad reasoning challenges creatively, from debugging logical inconsistencies to engineering solutions for edge-case scenarios, using iterative experimentation to uncover hidden potential in models. Evaluation and Iteration: Develop creative benchmarks and metrics to assess post-training impacts on reasoning, enabling rapid cycles of refinement that align with evolving user needs and technological frontiers. Collaborative Innovation: Partner with diverse teams to integrate post-training advancements into our AI ecosystem, leveraging your creativity to inspire cross-pollination of ideas and accelerate overall model intelligence.

About the company

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.

Skills

python
pytorch
ai
machine learning
deep learning
reasoning
problem-solving
research