AI Scientist - Agentic AI, R&D

Overview

The AI Scientist will design, prototype, and advance next-generation AI systems for clinical development, translational research, and broader pharmaceutical R&D, leveraging and extending AI approaches across the R&D lifecycle.

This role focuses on exploring and applying emerging AI methodologies to advance clinical and translational research, support data-driven decision-making, and improve R&D workflows. Relevant experience may come from clinical development, translational research, drug discovery, computational biology, or other data-intensive areas of pharmaceutical R&D.

The role will also involve integrating fragmented and heterogeneous biomedical data, transforming it into AI-ready datasets, and applying AI models to generate meaningful scientific insights across the drug development lifecycle.

The AI Scientist will contribute to the development of agentic AI systems, multi-agent workflows, and AI-driven scientific reasoning platforms that integrate advanced machine learning, large language models, and biomedical research applications.

The role requires a strong balance of AI research understanding, hands-on prototyping ability, and engineering execution, together with the ability to rapidly learn new scientific domains, collaborate with domain experts, and translate emerging ideas into scalable, production-ready solutions.

Responsibilities

Responsibilities include evaluating emerging AI techniques, reproducing and extending state-of-the-art research approaches, building experimental prototypes, and developing reusable AI system architectures that can be adapted across clinical development, translational research, drug discovery, and other pharmaceutical R&D use cases.

The AI Scientist will collaborate closely with cross-functional clinical, translational, discovery, data science, and engineering teams to identify high-impact opportunities where AI can meaningfully improve scientific reasoning, evidence generation, clinical research efficiency, and R&D decision-making.

The ideal candidate is highly technical, deeply curious about frontier AI capabilities, and able to quickly learn and operate across new scientific domains. We welcome candidates with strong AI experience in drug discovery, computational biology, translational research, clinical development, or adjacent biomedical fields who are excited to apply their expertise to new challenges across pharmaceutical R&D.

Prior experience specifically in clinical development or translational research is valued but not required. Candidates with strong AI/ML experience in drug development or adjacent biomedical domains and demonstrated ability to rapidly learn new scientific areas are strongly encouraged to apply.

Deep expertise in every stage of pharmaceutical R&D is not expected. Successful candidates will combine strong AI fundamentals with scientific curiosity and work closely with domain experts to develop the necessary clinical and translational context.

Qualifications

• Education: Master’s degree or higher in Computer Science, Artificial Intelligence, Machine Learning, Computational Biology, Bioinformatics, Biomedical Engineering, or a related quantitative or scientific discipline.
• Experience: At least 3 years of relevant experience in AI, machine learning, computational research, or applied R&D environments. Experience may come from pharmaceutical R&D, biotechnology, healthcare, or other scientifically intensive domains.
• AI Engineering Skills: Strong AI/ML engineering and coding skills, with hands-on experience rapidly prototyping, evaluating, and building robust AI applications and systems.
• Technical Stack: Strong programming skills in Python and hands-on experience with modern AI/ML frameworks and ecosystems such as PyTorch, Hugging Face, LangChain, LangGraph, LlamaIndex, or comparable tools. Ability to quickly evaluate and adopt new technologies is more important than experience with any specific framework.
• Domain Knowledge: Ability and willingness to rapidly learn new pharmaceutical R&D domains—including clinical development and translational research—and translate scientific questions into AI-enabled solutions. Prior experience in drug development, computational biology, or other biomedical R&D areas is highly transferable.
• Learning Agility / Scientific Adaptability: Demonstrated ability to rapidly learn unfamiliar scientific domains, formulate the right questions with subject-matter experts, and transfer AI methodologies across different research problems.
• Other Skills: Strong scientific curiosity, strategic thinking, problem-solving, and communication skills. Ability to work effectively with domain experts, rapidly learn unfamiliar scientific concepts, and thrive in a fast-paced, highly collaborative environment.
• English Proficiency: Professional-level English communication skills.
• Work Authorization: Applicants must be legally authorized to work in the United States. Visa sponsorship is not available for this position.

Preferred Qualifications

• AI-Assisted Development: Experience using AI-assisted development tools and workflows to accelerate experimentation, prototyping, and scientific problem-solving is highly desirable.
• Agentic AI: Strong interest or hands-on experience in agentic AI systems, multi-agent workflows, AI reasoning systems, and LLM-based applications; demonstrated ability to evaluate emerging AI approaches and apply them to new problem domains is highly valued.
• Biomedical Research: Experience applying AI/ML to biomedical, healthcare, life science, or other complex scientific datasets is highly desirable. Experience may span drug discovery, computational biology, translational research, clinical development, or adjacent scientific domains.
• Generative AI & LLMs: Experience with modern large language models, retrieval-augmented generation (RAG), tool use, structured reasoning, or AI workflow orchestration is a plus.
• Track Record: Experience applying AI to pharmaceutical R&D, healthcare, life sciences, or other complex scientific problems is advantageous. Relevant experience across drug discovery, translational research, and clinical development is valued; prior specialization in clinical or translational research is not required.

Compensation & Benefits

The anticipated salary range for this position is $135,000 - $160,000. Actual compensation may vary based on factors including experience, qualifications, skills, and business needs.

In addition to base salary, SK Life Science offers a competitive benefits package, including a 401(k) plan with company match and medical, dental, and vision coverage. Benefits are subject to eligibility requirements and may be modified at the Company's discretion.