Computational Chemistry & AI/ML Scientist

Marlabs Inc.; United States; On-site; USD 90,000 - 150,000; Full time

Job summary

Marlabs Inc. seeks a Computational Chemistry & AI/ML Scientist to advance molecular design, property prediction, and drug discovery using AI, ML, and cheminformatics.

You will collaborate with multidisciplinary teams to deploy models, simulations, and platforms that accelerate lead optimization and predictive modeling in a global pharma-relevant context. The role demands deep computational chemistry expertise, hands-on experience with AI/ML frameworks, and a track record of integrating molecular

Qualifications

• Ph.D. required in Computational Chemistry, Cheminformatics, Chemistry, Computer Science, Data Science, or related field; 1–3 years of industry/academic research in computational chemistry, AI/ML or molecular modeling.
• Strong expertise in deep learning frameworks and AI/ML including PyTorch, JAX, graph neural networks, transformers, generative models, and geometric deep learning for molecular applications.
• Hands-on experience deploying AI/ML models for molecular property prediction, molecular generation, lead optimization, drug discovery, or related scientific work.
• Strong computational chemistry background including molecular modeling, dynamics simulations, quantum chemistry; experience with Schrödinger Suite, MOE, AMBER, GROMACS, NAMD, PyMOL, or VMD.
• Proficiency in Python and scientific ecosystems (RDKit, Scikit-learn, Pandas, NumPy); Linux-based HPC environments.
• Excellent analytical and scientific communication skills; ability to work independently and cross-functionally.
• Preferred: experience in pharmaceutical, biotechnology, or life sciences research environments.

Responsibilities

• Design, develop, and deploy AI/ML models, including graph neural networks, transformers, generative models, and Bayesian optimization for molecular design and property prediction.
• Apply computational chemistry methods such as molecular modeling, dynamics, quantum chemistry, and structure-based modeling to support research.
• Build and optimize generative AI workflows for de novo molecular design, scaffold hopping, lead optimization, and multi-parameter optimization.
• Develop and maintain cheminformatics pipelines, molecular datasets, and model validation frameworks using Python and ML libraries.
• Collaborate with scientific, computational, and data teams to evaluate model performance, derive insights, and support drug discovery decisions.
• Deploy scalable AI and chem/ML workflows in cloud/HPC environments and drive continuous improvement of modeling capabilities.

Skills

Graph neural networks

Transformers

Generative AI models

Molecular property prediction

Molecular design

Molecular dynamics

Quantum chemistry

Python

PyTorch

JAX

Cloud / HPC workflows

Education

Ph.D. in Computational Chemistry, Cheminformatics, Chemistry, Computer Science, Data Science, or related field

Tools

Schrödinger Suite

MOE

AMBER

GROMACS

NAMD

PyMOL

VMD

RDKit

Scikit-learn

Pandas

NumPy

TensorFlow

PyTorch

Linux HPC

Job description

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled Computational Chemistry & AI/ML Scientist to join our innovative and dynamic team.

Employment Type: Full-time

Computational Chemistry & AI/ML Scientist | About You

As a Computational Chemistry & AI/ML Scientist, you will leverage advanced computational chemistry methodologies, machine learning, and generative AI technologies to accelerate molecular design, property prediction, and drug discovery research. You will collaborate closely with multidisciplinary scientific teams to develop and deploy cutting-edge AI/ML models, molecular simulation workflows, and computational platforms that support lead discovery, optimization, and predictive modeling initiatives. The ideal candidate combines deep expertise in computational chemistry with hands-on experience in modern AI/ML frameworks and molecular modeling technologies.

Computational Chemistry & AI/ML Scientist | Day-to-Day

• Design, develop, and deploy AI/ML models, including graph neural networks, transformers, generative models, and Bayesian optimization techniques for molecular property prediction and molecular design.
• Apply computational chemistry methodologies such as molecular modeling, molecular dynamics simulations, quantum mechanical calculations, and structure-based modeling to support research initiatives.
• Build and optimize generative AI workflows for de novo molecular design, scaffold hopping, lead optimization, and multi-parameter optimization challenges.
• Develop and maintain cheminformatics pipelines, molecular datasets, and model validation frameworks using Python and modern machine learning libraries.
• Collaborate with scientific, computational, and data science teams to evaluate model performance, generate actionable insights, and support decision-making throughout the drug discovery process.
• Deploy scalable AI and computational chemistry workflows within cloud and high-performance computing environments while supporting continuous improvement of modeling and simulation capabilities.

Computational Chemistry & AI/ML Scientist | Skills & Experience

• Ph.D. in Computational Chemistry, Cheminformatics, Chemistry, Computer Science, Data Science, or a related field, with 1-3 years of industry or academic research experience in computational chemistry, AI/ML, or molecular modeling.
• Strong expertise in deep learning and AI/ML frameworks, including PyTorch, JAX, graph neural networks, transformers, generative AI models, and geometric deep learning approaches for molecular applications.
• Hands-on experience developing and deploying AI/ML models for molecular property prediction, molecular generation, lead optimization, drug discovery, or related scientific applications.
• Strong computational chemistry background, including molecular modeling, molecular dynamics simulations, quantum chemistry, and experience with tools such as Schrödinger Suite, MOE, AMBER, GROMACS, NAMD, PyMOL, or VMD.
• Proficiency in Python and scientific computing ecosystems, including RDKit, Scikit-learn, Pandas, NumPy, TensorFlow, PyTorch, and Linux-based or high-performance computing environments.
• Strong analytical, scientific communication, and problem-solving skills, with the ability to work independently and collaborate effectively across multidisciplinary research teams.
• Preferred experience in pharmaceutical, biotechnology, drug discovery, or life sciences research environments.