Member of Technical Staff (Post Training)

About the Company

Inherent is a well-funded, fast-growing neo-lab dedicated to developing AI that explores “unknown unknowns” to uncover paradigm-shifting research contributions. We are building a new frontier lab focused on recursive self-improvement and human-machine teaming to reinvent the AI research factory.

Responsibilities

• Design, implement, and tune SFT and RL algorithms to post-train models that autonomously perform state-of-the-art research
• Build autocurricula, judges, harnesses, and eval pipelines to turn open-ended research tasks into reliable reward signals
• Run large-scale experiments on state-of-the-art hardware and analyze results to determine future hypotheses
• Close recursive loops so that AI agents drive their own post-training research
• Collaborate with Infrastructure and AI for Science teams to optimize hardware and performance

Requirements

• 3+ years of deep learning research experience
• Experience post-training large language, vision, video, or multi-modal models
• Demonstrated track record of success in deep learning research (papers, model releases, or open-source)
• 5+ years of software engineering experience
• Deep familiarity with Python and at least one deep learning framework (e.g., PyTorch, JAX)
• Experience using the latest coding agents

Preferred Qualifications

• PhD in mathematics, computer science, or a hard science discipline
• Hands-on experience training LLMs with RL at scale (GRPO/PPO, DPO, distillation)
• Familiarity with distributed and long-context training infrastructure
• Background in autocurricula, open-endedness, meta-learning, or recursive self-improvement
• Experience post-training frontier models at an industry lab