Applied AI Scientist
Harnham, Minneapolis, MN, United States
Applied AI Scientist
Harnham, the leading recruitment specialist in Data and AI, is partnering with a global technology organisation focused on advancing stateoftheart artificial intelligence through applied research. This organisation develops AIdriven solutions operating on complex, largescale data and is known for translating cuttingedge research into productiongrade systems used by professionals worldwide.
As an Applied AI Scientist, you will play a researchforward role at the intersection of applied machine learning science and realworld deployment. This position is ideally suited to a scientist who enjoys deep technical exploration, hypothesisdriven experimentation, and publishingquality 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: 6month 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 finetuning, promptbased learning, and hybrid symbolicneural 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 postgraduate experience in applied ML, NLP, IR, or Generative AI research.
Strong Python skills and experience with researchoriented prototyping.
Experience working with LLM-as-a-Judge
Indepth understanding of classical NLP/IR techniques and modern deep learning approaches.
Practical experience with transformerbased models and large language models.
Specific Technical Experience
Generative AI techniques including prompt engineering, incontext learning, controlled generation, and evaluation.
RetrievalAugmented Generation (RAG) pipelines and vector search.
Finetuning or pretraining language models.
Data curation, annotation strategies, and synthetic data generation.
Agentic AI frameworks such as LangGraph, AutoGen, or Semantic Kernel.
Cloudbased experimentation and deployment (AWS preferred; Azure or GCP acceptable).
If interested in this opportunity, please apply below
Harnham, the leading recruitment specialist in Data and AI, is partnering with a global technology organisation focused on advancing stateoftheart artificial intelligence through applied research. This organisation develops AIdriven solutions operating on complex, largescale data and is known for translating cuttingedge research into productiongrade systems used by professionals worldwide.
As an Applied AI Scientist, you will play a researchforward role at the intersection of applied machine learning science and realworld deployment. This position is ideally suited to a scientist who enjoys deep technical exploration, hypothesisdriven experimentation, and publishingquality 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: 6month 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 finetuning, promptbased learning, and hybrid symbolicneural 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 postgraduate experience in applied ML, NLP, IR, or Generative AI research.
Strong Python skills and experience with researchoriented prototyping.
Experience working with LLM-as-a-Judge
Indepth understanding of classical NLP/IR techniques and modern deep learning approaches.
Practical experience with transformerbased models and large language models.
Specific Technical Experience
Generative AI techniques including prompt engineering, incontext learning, controlled generation, and evaluation.
RetrievalAugmented Generation (RAG) pipelines and vector search.
Finetuning or pretraining language models.
Data curation, annotation strategies, and synthetic data generation.
Agentic AI frameworks such as LangGraph, AutoGen, or Semantic Kernel.
Cloudbased experimentation and deployment (AWS preferred; Azure or GCP acceptable).
If interested in this opportunity, please apply below