AI Engineer & Researcher - Reasoning 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

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.

Ideal Experience

• Post-Training Specialization: Extensive hands-on experience with post-training techniques (e.g., RLHF, DPO, or alignment methods) focused on reasoning improvements, with a portfolio of successful model enhancements.
• Creative Problem-Solving Prowess: Demonstrated ingenuity in solving ambiguous AI challenges, evidenced by innovative projects, research contributions, or unconventional approaches that yielded breakthroughs.
• Broad Technical Foundation: Proficiency in AI engineering tools (e.g., Python, PyTorch) and a solid grasp of model architectures, enabling you to navigate wide-ranging tasks from ideation to deployment.
• Research Versatility: Background in AI research with emphasis on reasoning, logic, or cognitive science, including publications or experiments that highlight creative applications in post-training contexts.
• Adaptable Expertise: 3+ years in multifaceted AI roles at cutting-edge organizations, where you've thrived in broad scopes by balancing creativity with rigorous execution to deliver high-impact results.

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.

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. 2x post-training technical sessions: These sessions will be testing your ability to formulate, design and solve concrete problems in training data for post-training.
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.

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. Researcher technical sessions (2): These sessions will be testing your ability to formulate, design and solve concrete problems in real world with LLM. It can be research or engineering, depending on background/experience.
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.

Annual Salary Range

$180,000 - $440,000 USD

xAI is an equal opportunity employer.

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