Applied AI Scientist

Role: Applied AI Scientist.Experience: 7+ yearsLocation: RemoteRequired Skills: ML, RAG, LLMs, Gen AI, Agentic AI, Applied Generative AIKey ResponsibilitiesAI Solution Development: Combine classical ML and cutting-edge Gen AI/agentic methods to solve key business challenges and drive operational efficiency.Proof-of-Concept & Experimentation: Plan and execute structured PoCs for Generative and Agentic AI systems—covering large-scale prompt optimization, fine-tuning, and model selection.Evaluation & Benchmarking: Design robust evaluation frameworks, define quantitative quality metrics, and construct benchmarks to test real-world AI performance.Quality & Safety Assurance: Establish groundedness, safety, and hallucination metrics to ensure trustworthy AI behavior.Model Analysis: Analyze foundation model behavior in dev/prod environments to identify failure modes, bias, and performance limits.Cross-Functional Collaboration: Translate complex AI concepts into clear, accessible insights for operational stakeholders and non-technical business partners.Agile Culture: Contribute to the AI Enablement operating model, adopting agile methodologies and building reusable AI best practices.What We’re Looking For:Education & ExperienceRequired: Bachelor’s degree in a STEM field with experience applying data science in a commercial setting.Preferred: Master’s degree or higher in a STEM field.Technical SkillsStrong foundation in statistical modeling and classical Machine Learning.Hands-on experience with GenAI methods: prompt engineering, RAG, fine-tuning strategies, and LLM output assessment.Experience building and operationalizing Agentic AI solutions.Proven track record designing evaluation frameworks, benchmark construction, A/B testing, and quality metrics.Excellent data visualization and technical communication skills.(Bonus) Familiarity with the Insurance domain or experience in a regulated industry.