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About the Role

Lila Sciences is seeking a Scientist, Computational Chemistry, Drug Discovery to guide, evaluate, and improve AI-driven drug discovery workflows. This role involves ensuring AI-generated plans and prioritizations are scientifically sound and contributing directly to drug discovery programs when computational chemistry leadership is needed. The position focuses on making agent-guided discovery scientifically useful and spans various computational chemistry tasks, including the design and supervision of tools for agentic workflows.

Responsibilities

Monitor and review drug discovery agents' computational chemistry workflows, recommendations, and optimization plans for scientific and chemical validity.
Evaluate agent-generated drug discovery plans for scientific coherence.
Advise on compound prioritization across discovery programs, considering various tradeoffs.
Define which computational chemistry tools agents should use, their inputs, and output interpretation.
Lead computational chemistry strategy for live drug discovery programs when needed.
Build, adapt, or guide the creation of open-source-first workflows for various computational chemistry tasks.
Apply protein-ligand binding modeling to support hypothesis generation, compound design, and prioritization.
Partner with cross-functional teams to improve AI-assisted discovery loops.
Evaluate agent-generated molecular design ideas and identify weaknesses.
Help establish validation standards, review protocols, and guardrails for computational chemistry tools used by AI systems.
Translate computational chemistry judgment into practical requirements for agent tools, workflows, benchmarks, and decision criteria.

Requirements

PhD or equivalent experience in computational chemistry, chemistry, cheminformatics, molecular modeling, biophysics, or a related field.
Strong practical experience applying computational chemistry in a drug discovery context, including active program support or leadership.
Demonstrated history of modeling protein-ligand binding and using those models to inform discovery decisions.
Working knowledge across docking, virtual screening, SAR modeling, conformer generation, pharmacophore modeling, QSAR, ADMET or property prediction, and cheminformatics.
Strong medicinal chemistry experience and the ability to reason about compound optimization, SAR, developability, and synthetic or experimental tradeoffs.
Fluency in Python and hands-on experience building open-source computational chemistry workflows with libraries such as RDKit, Biopython, OpenMM, MDAnalysis, or comparable tools.
Ability to evaluate computational recommendations critically and communicate uncertainty, assumptions, and limitations clearly.
Comfort working alongside AI systems, including reviewing, guiding, and improving agent-generated plans.
Strong collaboration skills across chemistry, biology, ML, computational science, and engineering teams.

Skills

Computational Chemistry
Drug Discovery
AI-driven workflows
Compound prioritization
Modeling workflows
Docking
Virtual screening
SAR modeling
Molecular property prediction
Medicinal chemistry support
Live program support
Python
RDKit
Biopython
OpenMM
MDAnalysis
Protein-ligand binding modeling
Cheminformatics
FEP
MM/GBSA
Molecular dynamics

Location

U.S.

Work Type

Full-time

Experience Level

PhD or equivalent experience
Strong practical experience
Demonstrated history
Working knowledge
Strong medicinal chemistry experience
Hands-on experience
Comfort working alongside AI systems
Strong collaboration skills
Industry drug discovery experience (bonus)
Experience extending, integrating, or contributing to open-source scientific software (bonus)
Experience with FEP, MM/GBSA, molecular dynamics, or other physics-based scoring workflows (bonus)
Experience integrating computational chemistry workflows into automated or agentic systems (bonus)
Exposure to DEL, high-throughput screening, or other large experimental datasets (bonus)
Experience with prospective compound prioritization in active discovery programs (bonus)

Education Level

PhD or equivalent experience in computational chemistry, chemistry, cheminformatics, molecular modeling, biophysics, or a related field.

Salary/Compensations

$140,800—$217,800 USD

Benefits

Competitive base compensation with bonus potential
Generous early-stage equity
Medical, dental, and vision coverage
Employer-paid life and disability insurance
Flexible time off with generous company wide holidays
Paid parental leave
Educational assistance program
Commuter benefits, including bike share memberships for office based employees
Company subsidized lunch program
Comprehensive benefits program tailored to their region (International)

About the Company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges.
We believe science is the most inspiring frontier for AI.
LILA builds systems that can learn for themselves.
LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy.
Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance.

Equal Opportunity

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.