AI Engineer & Researcher - Reasoning Post-training
Skills
- Expertise with post-training techniques like RLHF, DPO, or alignment methods focused on reasoning.
- Strong programming skills in Python and experience with AI frameworks such as PyTorch.
- Profound understanding of AI model architectures and reasoning, logic, or cognitive science principles.
- Creative problem-solving with demonstrated research or engineering contributions.
- Excellent communication and collaboration skills.
Responsibilities
- Apply and innovate on post-training optimization techniques such as fine-tuning, reinforcement learning variants, and data augmentation.
- Design creative methodologies including custom prompting frameworks and synthetic reasoning datasets to improve model cognition.
- Explore and solve broad reasoning challenges through iterative experimentation and debugging logical inconsistencies.
- Develop and implement novel benchmarks and metrics to evaluate post-training effects on reasoning capabilities.
- Collaborate with cross-functional teams to integrate post-training advancements into the AI ecosystem.
Education
- Advanced degree in Computer Science, AI, Machine Learning, Cognitive Science, or related field preferred.
Benefits
- Competitive salary range from $180,000 to $440,000 annually.
- Hybrid work model with mostly onsite presence in Palo Alto and flexibility for remote days.
- Opportunity to work in a flat, initiative-driven organization emphasizing engineering excellence and innovation.
Average salary estimate
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