Lead Applied AI Researcher

Join our team as a Lead Applied AI Researcher in the energy sector. In this role, you will design experiments to optimize AI models for various workloads, own our evaluation framework, explore post-training methods, and build reliable agent harnesses. You will work closely with teams across the company to turn research results into production systems. The ideal candidate will have hands-on experience with model selection, fine-tuning, reinforcement learning, and strong software engineering skills.

About Fuse Energy

Concevoir des expériences pour trouver le meilleur modèle et l'approche pour chaque charge de travail, en équilibrant précision, latence et coût.

Responsibilities

• Posséder notre cadre d'évaluation : construire des ensembles de données de haute qualité et des réponses d'or, combiner les jugements humains et ceux des LLM.
• Explorer les méthodes post-formation, y compris le fine-tuning supervisé et l'apprentissage par renforcement.
• Hands-on experience with several of model selection and routing, fine-tuning, reinforcement learning, agent systems or computer use

Requirements

• Good judgment about cost, latency, reliability and risk, especially when deciding where deterministic checks or human review are needed
• Strong software engineering skills, including Python and the ability to build reliable experimental and production tooling
• Ability to move between research and implementation: formulate a hypothesis, run a rigorous test, inspect failures and ship what works
• Deep understanding of evaluations, dataset quality and failure analysis. You know how to distinguish a genuine improvement from an unreliable benchmark result
• Strong experience applying modern AI models to real-world tasks with a track record of improving measured outcomes through experimentation

Preferred

• Experience at a frontier AI lab or a team operating at a similar level of experimentation would be especially valuable