Research Senior Scientist, Cheminformatics AI/ML

Scorpion Therapeutics; Boston (MA); On-site; USD 137,000 - 215,000; Full time

Benefits offered by this job

Medical/dental/vision insurance

401(k) match

Tuition reimbursement

Volunteer time off

Holidays and paid vacation

Well-being benefits

Sick time

Paid vacation

Job summary

Scorpion Therapeutics in Boston is seeking a skilled cheminformatic scientist to join the cheminformatics team. You will integrate cheminformatics, computational chemistry, and ML to accelerate drug design and collaborate with medicinal chemistry, DMPK, and AI/ML groups to define a roadmap for computational tools.

Apply your expertise in agentic AI, MLOps, and large chemical databases to build scalable workflows, design molecular design/optimization models, and support translational workflows

Qualifications

• PhD in a relevant field; 2+ years in pharma/biotech.
• Experience developing agentic AI systems for drug discovery and integrating databases, foundation models, and multi-step workflows.
• Hands-on MLOps/model lifecycle management (orchestration, CI/CD, registries, monitoring, version control, cloud/HPC deployment).
• Experience building/searching ultra-large chemical databases; familiarity with cloud storage, vector search, and chemical indexing.
• Programming/scripting: Python, R, C/C++; ability to design/automate scalable workflows.
• Strong cheminformatics toolkit expertise (RDKit); comprehensive DMTA-cycle knowledge; leading acceleration initiatives.

Responsibilities

• Develop and apply agentic AI solutions for drug discovery, including autonomous or human-in-the-loop workflows.
• Identify opportunities across the DMTA cycle for predictive acceleration; build models for molecule design/optimization and extract medchem knowledge.
• Establish and maintain MLOps capabilities: reproducible training/deployment pipelines, lifecycle orchestration, performance monitoring, versioning, retraining.
• Build and enable search/analytics across ultra-large chemical databases (scalable ingestion, standardization, indexing, similarity/substructure search, distributed computing).
• Implement innovative computational methods for drug discovery (AI-based discovery, generative chemistry, space exploration, DEL data analysis).
• Act as a trusted thought partner to ideate and execute chemistry strategies aligned to therapeutic goals.

Skills

Python

R

C/C++

RDKit

MLOps

DMTA-cycle

Education

PhD in Computational Chemistry, Cheminformatics, Computer Science, or related field

Tools

CI/CD pipelines

Cloud platforms

Vector search

Job description

Objective / Purpose:

• Skilled cheminformatic scientist to join cheminformatics team to foster a “prediction-first” culture by integrating cheminformatics, computational chemistry, and machine learning to accelerate drug design.
• Collaborate with medicinal chemistry, DMPK, and AI/ML teams; define a roadmap for computational tools that empower medicinal chemists.

Accountabilities:

• Develop and apply agentic AI solutions for drug discovery, including autonomous or human-in-the-loop workflows integrating scientific reasoning, molecular design/optimization and data analysis, and computational tools.
• Identify opportunities across the DMTA cycle for predictive acceleration; build models for molecule design/ optimization and extract medchem knowledge from chemical/biological datasets.
• Establish and maintain MLOps capabilities: reproducible training/deployment pipelines, lifecycle orchestration, performance monitoring, versioning, scheduled retraining.
• Build and enable search/analytics across ultra-large chemical databases (scalable ingestion, standardization, indexing, similarity/substructure search, distributed computing).
• Implement innovative computational methods for drug discovery (AI-based discovery, generative chemistry, synthesizable chemical space exploration, DEL data analysis, DEL/ML).
• Act as a trusted thought partner to ideate and execute chemistry strategies aligned to therapeutic goals.

Qualifications:

• PhD in Computational Chemistry, Cheminformatics, Computer Science, or related field; 2+ years in pharma/biotech.
• Experience developing agentic AI systems for drug discovery and integrating/orchestrating chemical/biological databases, foundation models, scientific software tools, and multi-step workflows.
• Hands-on MLOps/model lifecycle management (orchestration, CI/CD, registries, monitoring, version control, deployment in cloud or HPC).
• Experience building/searching ultra-large chemical databases; familiarity with cloud storage, vector search, and chemical indexing desired.
• Programming/scripting: Python, R, C/C++; ability to design/automate scalable workflows.
• Strong cheminformatics toolkit expertise (e.g., RDKit); comprehensive DMTA-cycle knowledge; experience leading DMTA acceleration initiatives.

Benefits:

• U.S. base salary range: $137,000.00–$215,270.00 (plus potential incentives and benefits such as medical/dental/vision, 401(k) match, disability, life insurance, tuition reimbursement, volunteer time off, holidays, well-being benefits, sick time, and paid vacation).