Applied AI Researcher

b Overview /b p In this role you will advance AI at Fuse to improve energy systems. You will design experiments to optimize models for accuracy, latency and cost, and lead the evaluation framework with high-quality datasets and human/LLM judgments. You will develop post-training methods, build reliable agent frameworks, and set failure thresholds. You will collaborate with cross-functional teams to deploy research as production systems, translating frontier AI insights into real-world impact. This role offers the chance to help make energy cheaper and more abundant through AI and to work at the cutting edge of applied AI in energy. /p b Pay / Benefits /b ul li Competitive salary and equity /li li Biannual bonus scheme /li li Fully expensed tech /li li Private health insurance /li li Breakfast and dinner allowance for office-based employees /li /ul b Responsibilities /b ul li Design experiments to find the best model and approach for each workload, balancing accuracy, latency and cost /li li Own evaluation framework: build datasets and golden answers, combine human and LLM judgments, measure confidence in evaluators /li li Explore post-training methods including supervised fine-tuning and reinforcement learning /li li Build agent harnesses to support long-running tasks: tool use, checks, state tracking, retries, resource allocation, human approvals /li li Set evaluation and escalation thresholds based on failure consequences /li li Collaborate across Fuse to turn research into production systems and share lessons from frontier AI /li /ul b Key requirements /b ul li Strong experience applying modern AI models to real-world tasks with improved outcomes through experimentation /li li Deep understanding of evaluations, dataset quality and failure analysis /li li Hands-on experience with model selection and routing, fine-tuning, reinforcement learning, agent systems or computer use /li li Strong software engineering skills, including Python and building reliable experimental and production tooling /li li Good judgment on cost, latency, reliability and risk, especially for deterministic checks or human review /li li Ability to move between research and implementation: formulate a hypothesis, test, inspect failures, ship working solutions /li li Experience at a frontier AI lab or high-experimentation team would be valuable /li /ul ul li cross-functional collaboration /li li analytical mindset /li li strong judgment /li li Python /li li model selection and routing /li li fine-tuning /li /ul