AI & LLM Applications Scientist

InVitro Cell Research; Northern (KY); On-site; USD 155,000 - 215,000; Full time

Job summary

InVitro Cell Research is seeking an AI & LLM Applications Scientist to augment scientists’ workloads and accelerate research in regenerative medicine. You will design AI-enabled workflows with bench scientists and data scientists, prototype tools, and deploy models to improve throughput and rigor.

You'll lead training to raise AI literacy across the organization, stay current with AI advances, and advise on build vs buy decisions aligned with ICR's mission.

Qualifications

• Extensive hands-on experience with modern AI and LLMs.
• Strong technical foundation in computer science, ML, or data science or equivalent experience in scientific domains.
• Understanding of LLM capabilities, limitations, and mitigation strategies.
• Experience translating problems into AI-enabled solutions with non-technical stakeholders.
• Experience designing experiments to evaluate AI tools (A/B testing, human-in-the-loop).
• Excellent communication skills to explain AI concepts to varied audiences.
• Interest in regenerative medicine, aging biology, or age-related diseases; Python proficiency.

Responsibilities

• Partner with bench scientists and data scientists to design AI/LLM-enabled workflows.
• Evaluate, prototype, and deploy AI tools to accelerate research programs.
• Co-create AI-assisted solutions to increase throughput and scientific rigor.
• Design and deliver training sessions to raise AI literacy across ICR.
• Monitor AI landscape and advise leadership on build/buy/adopt decisions.

Skills

AI & LLMs expertise

Prompt engineering

Machine learning fundamentals

Python programming

Communication skills

Experiment design

Collaboration with scientists

Education

CS/ML/Data Science background

Tools

Vector databases

Open-source LLMs

Job description

We’re hiring AI & LLM Applications Scientists to help augment and accelerate ICR scientists’ workloads, improving both quality and productivity across the organization. The ideal candidate has a deep, practical understanding of modern AI and large language models, including how they work, what they can and cannot do, and how to most wisely integrate and deploy them in a fast-paced scientific environment.

Our ideal candidate not only knows how to use AI and LLMs, but understands them at a fundamental level — their core principles, limitations, and what truly makes them work. The candidate will have a similarly deep, first‑principles grasp of deep learning, neural networks, machine learning, and modern software and computing, not just surface‑level familiarity. Their ability to clearly articulate the underlying ideas and “essence” of these systems to others will be a key indicator of this depth of understanding and will be vital to the success of this role within our company.

With us, you'll get to:

• Partner with bench scientists, computational biologists, and data scientists to design and implement AI/LLM‑enabled workflows that streamline literature review, study design, data interpretation, and reporting.
• Evaluate, prototype, and deploy AI tools (including frontier and open‑source models) to accelerate ICR’s research programs in regenerative and preventive medicine, with a focus on aging and age‑related diseases.
• Work directly with individual scientists and teams to understand their pain points, then co‑create AI‑assisted solutions that measurably increase throughput and scientific rigor.
• Design and deliver training sessions and small‑group workshops to raise AI literacy across all levels of ICR, from junior scientists to senior leadership.
• Continuously monitor the AI landscape, benchmarking new models and tools, and advise leadership on build/buy/adopt decisions aligned with ICR’s mission and risk tolerance.

Please apply if you have:

• Extensive hands‑on experience with modern AI and LLMs (e.g., GPT‑class models, open‑source LLMs, multimodal models), including prompt engineering, evaluation, and workflow integration.
• A strong technical foundation in computer science, machine learning, data science, or a closely related field; or equivalent experience applying AI in scientific or technical domains.
• Demonstrated understanding of LLM capabilities and limitations, including hallucinations, bias, privacy and IP concerns, security, and appropriate mitigation strategies.
• Experience partnering with non‑technical individuals to translate loosely defined scientific or organizational problems into concrete AI‑enabled solutions.
• Experience designing or running experiments to evaluate AI tools including but not limited to A/B testing, human‑in‑the‑loop evaluation, metrics for quality, reliability, and productivity impact).
• Excellent communication skills and the ability to explain complex AI concepts clearly to audiences with a wide range of technical backgrounds.
• A strong interest in regenerative medicine, aging biology, or age‑related diseases, and enthusiasm for using AI to advance ICR’s mission.
• An understanding of basic machine learning paradigms and scoring rules.
• Extensive programming experience (Python preferred).

Ideally, you'll also experience with:

• Working with scientific or biomedical data (e.g., omics, imaging, clinical, or real‑world data) and understanding their common pitfalls and preprocessing requirements.
• Using vector databases, retrieval‑augmented generation (RAG), or fine‑tuning approaches to adapt foundation models to domain‑specific use cases.
• Building or curating evaluation datasets and annotation guidelines for scientific or technical AI applications.

And you'll need:

• The ability to work in the United States without sponsorship.
• Comfort operating in a fast‑moving AI landscape, including the humility to say “I don’t know yet” and the discipline to test assumptions before broad deployment.
• To have an easygoing, hard-working personality.

Starting base pay range: $155,000/yr - $215,000/yr

Starting additional compensation range: $10,000/yr - $20,000/yr

Starting position title and compensation are commensurate with experience.