Applied Scientist

Applied AI Scientist Harnham, the leading recruitment specialist in Data and AI, is partnering with a global technology organisation focused on advancing state‑of‑the‑art artificial intelligence through applied research. This organisation develops AI‑driven solutions operating on complex, large‑scale data and is known for translating cutting‑edge research into production‑grade systems used by professionals worldwide. As an Applied AI Scientist, you will play a research‑forward role at the intersection of applied machine learning science and real‑world deployment. This position is ideally suited to a scientist who enjoys deep technical exploration, hypothesis‑driven experimentation, and publishing‑quality rigor, while still seeing their work influence tangible products. The work centres on Generative AI, Agentic AI, and advanced NLP and Information Retrieval systems. Details • Location: Eagan, MN (Hybrid – 2–3 days onsite) • Contract Length: 6‑month initial engagement (extendable) • Hours: 40 hours per week • Engagement Type: W2 or C2C • Start Date: June • Compensation: Competitive and flexible depending on experience Responsibilities • Conduct applied research across NLP, Generative AI, and Agentic systems, with an emphasis on empirical evaluation and methodological rigor. • Design controlled experiments to evaluate novel modelling approaches, architectures, and retrieval strategies. • Explore and prototype new techniques involving large language models, including fine‑tuning, prompt‑based learning, and hybrid symbolic‑neural methods. • Maintain reproducible research pipelines, including dataset versioning, experiment tracking, and evaluation frameworks. • Translate research findings into technical recommendations and roadmaps. Technical Requirements • MSc or PhD in Computer Science, AI, Machine Learning, Statistics, Engineering, or related discipline (or equivalent experience). • 3+ years of post‑graduate experience in applied ML, NLP, IR, or Generative AI research. • Strong Python skills and experience with research‑oriented prototyping. • Experience working with LLM-as-a-Judge • In‑depth understanding of classical NLP/IR techniques and modern deep learning approaches. • Practical experience with transformer‑based models and large language models. Specific Technical Experience • Generative AI techniques including prompt engineering, in‑context learning, controlled generation, and evaluation. • Retrieval‑Augmented Generation (RAG) pipelines and vector search. • Fine‑tuning or pre‑training language models. • Data curation, annotation strategies, and synthetic data generation. • Agentic AI frameworks such as LangGraph, AutoGen, or Semantic Kernel. • Cloud‑based experimentation and deployment (AWS preferred; Azure or GCP acceptable). If interested in this opportunity, please apply below