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Salary: USD 160,000 - 220,000 / annual
Antares Therapeutics, a venture-backed precision medicine company, is seeking a Senior Scientist to develop and deploy LLM-driven agents for scientific workflows in drug discovery. You will work embedded with discovery project teams—medicinal chemists, chemical biologists, computational scientists, and ML engineers—to identify and build agentic systems that accelerate design-make-test-analyze cycles and sharpen program decisions.
Key responsibilities include:
• Embed with discovery teams as the AI enablement partner, identifying where agents can accelerate cycles and influence go/no-go decisions.
• Build and maintain Model Context Protocol (MCP) servers and tool integrations connecting LIMS/ELN, structural, assay, and DMPK data to agentic workflows, respecting data permissions so scientists can interrogate internal data directly.
• Develop and deploy LLM-driven agents and multi-agent systems orchestrating tools and models for assay data analysis, SAR interpretation, target assessments, DMPK understanding, and competitive intelligence.
• Own evaluation and benchmarking of deployed systems with sound MLOps practices—defining task-specific benchmarks, running error analysis, and tracking accuracy and reliability so outputs inform critical decisions.
• Develop reusable skills for LLM-based tools and reference implementations so solutions built for one program serve the entire portfolio.
• Analyze and integrate cross-functional data to independently identify and address scientific questions; communicate approaches, limitations, and recommendations clearly to teams and leadership.
• Act as the AI enablement function lead on programs, establish internal best practices, and evaluate emerging platforms and methods.
This is a hands-on individual-contributor role on Antares' scientific track. The role is offered at Senior Scientist I or II level; scope and cross-functional influence scale with experience. You will have direct impact on a lean discovery organization's capability to make faster, better-informed decisions.
Qualifications: PhD in computational chemistry/biology, cheminformatics, computer science, machine learning, or related quantitative field (or equivalent). Senior Scientist I requires 5+ years post-PhD (or 13+ with bachelor's); Senior Scientist II requires 8+ years post-PhD (or 16+ with bachelor's) with demonstrated independent delivery and cross-functional influence.
Essential: direct contributions to small-molecule drug discovery programs in pharma/biotech where your work measurably influenced design decisions. Hands-on development and deployment of LLM-driven agents and multi-agent systems using current frameworks and frontier models (Claude, GPT, etc.). Strong Python programming and fluent use of coding agents. Experience with model evaluation, benchmarking, and MLOps for reliable deployment. Working knowledge of medicinal chemistry, SAR, structural biology, and DMPK principles. Familiarity with cheminformatics toolkits (RDKit, OpenEye, Schrödinger) strongly preferred.
