[ SK Life Science ] AI Scientist, Agentic AI Discovery

Korean American Society in Biotech and Pharmaceuticals

Paramus (NJ)

On-site

USD 100,000 - 130,000

Full time

14 days+

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Job summary

The Korean American Society in Biotech and Pharmaceuticals is seeking an AI Scientist in Paramus, New Jersey. This critical role involves designing and advancing AI systems for drug discovery, leveraging emerging AI methodologies to enhance research workflows.

The ideal candidate holds a Master's degree and has over 3 years of applicable experience in AI and machine learning, along with strong programming skills in Python and familiarity with AI frameworks like PyTorch and Hugging Face. The position offers a full-time opportunity to impact the field of pharmaceuticals through innovative AI solutions.

Qualifications

  • Minimum 3 years of experience in AI and machine learning.
  • Experience with agentic AI systems and multi-agent orchestration.
  • Strong strategic thinking and problem-solving skills.

Responsibilities

  • Design and prototype next-generation AI systems for drug discovery.
  • Collaborate with research teams to improve discovery efficiency.
  • Evaluate and extend state-of-the-art research approaches.

Skills

AI Engineering Skills
Strong programming skills in Python
Experience with AI-assisted development
Interest in agentic AI systems
Experience with biomedical datasets
Knowledge of generative AI & LLMs

Education

Master’s degree or higher in AI-related fields

Tools

PyTorch
Hugging Face
LangChain

Job description

SK Life Science AI Scientist, Agentic AI Discovery

AI Scientist, Agentic AI Discovery (1 position)

  • Work location: Paramus, New Jersey
  • Employment type: Full‑time
Role Description

The AI Scientist will design, prototype, and advance next‑generation AI systems for drug discovery and pharmaceutical research. This role focuses on exploring and applying emerging AI methodologies to accelerate scientific discovery, support data‑driven decision‑making, and improve R&D workflows across drug discovery programmes.

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 to rapidly evaluate new ideas and translate them into scalable, production‑ready solutions.

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 support scientific exploration and therapeutic discovery. The AI Scientist will collaborate closely with cross‑functional research and engineering teams to identify high‑impact opportunities where AI can meaningfully improve discovery efficiency and insight generation. The ideal candidate is highly technical, deeply curious about frontier AI capabilities, and excited about applying advanced AI systems in real‑world drug discovery environments.

Qualifications
  • Education: Master’s degree or higher in AI‑related fields, Computer Science, Computational Biology, Bioinformatics, Machine Learning, or related disciplines.
  • Experience: At least 3 years of relevant experience in AI, machine learning, or applied research environments.
  • Work Authorization: Applicants must be legally authorized to work in the United States. Visa sponsorship is not available for this position.
  • AI Engineering Skills: Strong AI engineering and coding skills, with hands‑on experience building scalable and production‑ready AI applications and systems.
  • AI‑Assisted Development: Experience with AI‑assisted development and rapid prototyping workflows (“vibe coding”) is highly desirable.
  • Agentic AI: Strong interest or hands‑on experience in agentic AI systems, multi‑agent orchestration frameworks, AI reasoning workflows, and LLM‑based applications.
  • Biomedical Research: Experience working with biomedical or life science datasets and AI‑driven scientific research platforms is highly desirable.
  • Generative AI & LLMs: Experience working with modern large language model ecosystems, prompt engineering, retrieval‑augmented generation (RAG), or AI workflow orchestration frameworks is a plus.
  • Technical Stack: Strong programming skills in Python and familiarity with modern AI/ML frameworks such as PyTorch, Hugging Face, LangChain, LangGraph, LlamaIndex, or similar ecosystems.
  • Domain Knowledge: Ability to quickly learn and understand drug discovery and pharmaceutical R&D domains and connect them with AI solutions.
  • Other Skills: Strong strategic thinking, problem‑solving, interpersonal, and communication skills. Ability to excel in a fast‑paced, startup‑like environment with a focus on innovation and adaptability.
  • Track Record: Experience applying AI within drug discovery, healthcare, or life sciences is advantageous.
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