{"id":4052549,"url":"https://alion.io/job/marlabs-ai-scientist-molecular-machine-learning","title":"AI Scientist – Molecular Machine Learning","company":{"id":454698,"name":"Marlabs","domain":"marlabs.com","url":"https://alion.io/company/marlabs","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Diffusion Models","optional":false},{"name":"JAX","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"Mixture of Experts","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Transformers","optional":false}],"status":"live","first_seen_at":"2026-11-10T22:34:17Z","employer_posted_date":null,"last_verified_at":"2026-11-10T22:34:17Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"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 AI Scientist – Molecular Machine Learning to join our innovative and dynamic team.\n\nAI Scientist – Molecular Machine Learning | About You\n\nAs an AI Scientist – Molecular Machine Learning, you will design and develop advanced AI/ML models that accelerate molecular property prediction, molecular generation, and drug discovery. You will apply deep learning, graph neural networks, geometric learning, transformers, and generative AI to complex molecular and chemical datasets, partnering closely with computational chemists and drug discovery scientists to solve high-impact scientific challenges. The ideal candidate is an AI/ML-first scientist with strong model development expertise and demonstrated experience applying machine learning to chemistry, molecular design, or drug discovery.\n\nAI Scientist – Molecular Machine Learning | Day-to-Day\n\nDesign, develop, train, and evaluate deep learning models for molecular property prediction, molecular generation, and drug discovery applications.\n\nBuild molecular AI solutions using Graph Neural Networks (GNNs), Graph Transformers, geometric deep learning, and generative modeling techniques.\n\nDevelop scalable AI/ML workflows using Python, PyTorch and/or JAX, optimizing models for accuracy, efficiency, and scientific relevance.\n\nBuild and manage molecular datasets and cheminformatics workflows using RDKit and related tools, including molecular representation, preprocessing, feature generation, and model-ready dataset development.\n\nDevelop generative modeling approaches for de novo molecular design, lead optimization, and molecular exploration, leveraging techniques such as diffusion models, flow matching, reinforcement learning, or related architectures.\n\nCollaborate with computational chemists, medicinal chemists, and drug discovery scientists to translate scientific problems into AI/ML approaches and generate actionable insights for molecular discovery programs.\n\nEvaluate and continuously improve molecular ML models using rigorous experimentation, validation, benchmarking, and reproducible research practices.\n\nAI Scientist – Molecular Machine Learning | Skills & Experience\n\nPh.D. in Computer Science, AI/ML, Computational Chemistry, Cheminformatics, Data Science, Physics, or a related technical or scientific discipline, with relevant experience applying AI/ML to molecular or scientific problems.\n\nStrong hands-on expertise with PyTorch and/or JAX, including developing, training, evaluating, and optimizing deep learning models.\n\nDemonstrated experience with Graph Neural Networks, Graph Transformers, geometric deep learning, and generative AI, particularly for molecular representation, property prediction, or molecular design.\n\nStrong Python programming and cheminformatics experience, including RDKit or comparable toolkits, with experience working with complex molecular datasets.\n\nExperience applying AI/ML to molecular property prediction, molecular generation, drug discovery, ADMET modeling, lead optimization, or related molecular science applications.\n\nExperience working within Linux and high-performance computing environments, with exposure to tools such as Schrödinger, MOE, GROMACS, OpenMM, or other molecular modeling platforms considered valuable.\n\nOriginally posted on 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