Principal Agentic Scientist

Insilico Search Partners; Boston (MA); Hybrid; USD 208,000 - 275,000; Full time

Job summary

Insilico Search Partners is seeking a Principal Scientist to design and lead agentic AI/ML systems across drug discovery, from target ID through translational and clinical development.

You will architect scalable agentic workflows integrating genomics, protein design, multi-omics, and literature mining into end-to-end pipelines trusted by scientists daily.

Qualifications

• 5+ years applying AI/ML in pharma or biotech settings.
• Proven ability to lead agentic AI/ML projects end-to-end, from design to production.
• Strong Python skills with PyTorch or JAX/TensorFlow.
• Experience with LLM platforms (Anthropic, OpenAI, Vertex AI, Bedrock) a plus.

Responsibilities

• Lead the design, orchestration, and scaling of agentic AI systems.
• Own build, benchmarking, and maintenance of agentic pipelines.
• Mentor scientists and engineers; support recruiting as the ML function grows.
• Track and translate emerging agentic AI/ML literature into build strategies.
• Communicate complex technical work to executives.

Skills

Python

PyTorch

JAX/TensorFlow

Leadership

Agentic AI/ML

Executive communication

Education

MS or PhD in Machine Learning/Computational Biology

Tools

LangGraph

CrewAI

AutoGen

Pydantic AI

Job description

Principal Scientist, Agentic AI/ML Systems — Drug Discovery

Machine Learning | Remote-Hybrid, once a month travel | Cambridge, MA

$208,000 – $275,000

About the Opportunity

A fast-growing, AI-first, venture organization focused on accelerating pharmaceutical R&D is seeking a Principal Scientist to architect and lead agentic AI/ML systems across the drug discovery space, from target ID through translational and clinical development. This is a chance to build the foundation of LLM-based agents and agentic workflows, that ties genomics, protein design, multi-omics, cheminformatics, and literature mining into unified, end-to-end pipelines scientists rely on daily.

The Role

Lead the design, orchestration, and scaling of agentic AI systems that automate and accelerate computational biology workflows. Partner with venture and platform leadership to define pragmatic AI strategy, own technical execution, and set the benchmarking and evaluation bar for agentic systems.

What You'll Own

• Program Leadership: Lead multiple AI/ML and computational programs spanning preclinical, translational, and clinical R&D.
• Agentic System Architecture: Design, build, and scale agentic systems (LangGraph, CrewAI, AutoGen, Pydantic AI) that orchestrate ML and comp-bio tools — genomics, biomolecule design, docking, multi-omics, literature mining — into automated end-to-end scientific workflows.
• Technical Ownership: Own build, benchmarking, evaluation, and maintenance of agentic pipelines, including sandboxed code execution, agent harness development, and observability/cost-governance tooling.
• Team Leadership: Manage and mentor scientists/engineers; support recruiting and interviewing as the ML function grows.
• Strategy & Landscape: Track emerging agentic-AI/ML literature; translate it into build strategies that accelerate R&D.
• Communication: Translate complex technical work for cross-functional and executive audiences to drive decisions.

What You Bring

• MS or PhD in Machine Learning, Statistics, Computational Biology, or a related field, with 5+ years applying AI/ML in academic, pharma, or biotech settings.
• Demonstrated ability to lead agentic AI/ML projects end-to-end, from architecture to production.
• Strong Python and modern ML framework depth (PyTorch or JAX/TensorFlow).
• Track record of publications, patents, or high-impact technical delivery.
• Preferred: hands‑on integration of LLM platforms (Anthropic, OpenAI, Vertex AI, Bedrock) and evaluation/feedback‑loop frameworks for agentic systems; breadth across genomics, protein design, proteomics, cheminformatics/ADMET, or biophysics.