Job Description

About Ten63 TherapeuticsApply now, read the job details by scrolling down Double check you have the necessary skills before sending an application.Ten63 Therapeutics is focused on improving human health by developing better, more durable therapeutics against cancer and some of the world's most lethal diseases. We are leveraging our proprietary in silico platform BEYOND to generate novel therapeutics to hit previously undruggable targets. We're pioneering an engineered approach to drug discovery by scaling quantum simulations and fusing them with generative chemistry to tackle previously undruggable, high-impact targets. Our team of pioneering scientists, engineers, drug hunters, and quantum chemists values passion, teamwork, out-of-the-box thinking and determination to solve even what seems impossible. Position OverviewWe are seeking an exceptional Senior ML Scientist to join our team of pioneering scientists, engineers, drug hunters and quantum chemists. This role requires a unique combination of deep expertise in state-of-the-art deep learning techniques and physics-based molecular simulations to develop the AI models powering Ten63's BEYOND platform. You will design and train sophisticated deep learning architectures and lead model development for our computational chemistry workflows, and work with our AI engineers to promote validated models into production software environments. As a key technical liaison, you will sit at the nexus of computational chemistry, software engineering, and drug development, translating complex scientific requirements into robust AI-driven solutions.Key ResponsibilitiesDesign, implement, and train deep learning models for a variety of drug-design applications, using a variety of cutting-edge architectures, including transformers, diffusion networks, GANs, flow networks, etc. (Note that equal levels of familiarity with all the architectures mentioned above is not expected.)Lead large-scale model training efforts on multi-GPU compute clusters, including experiments that span weeks to monthsDesign methods that couple physics-based simulation (molecular dynamics, quantum calculations, Monte Carlo methods) with learned modelsPrototype and develop methods for using the models you build in structure-based drug designDesign the datasets, splits, and benchmarks that models are trained and evaluted on — which data, which labels, and which held-out sets reflect real prospective use across protein structures, small molecules, molecular descriptors, and simulation trajectoriesDesign validation that reflects prospective use, including scaffold and temporal splits, applicability domain, and calibrated uncertainty, and be candid about where a model should not be trustedPartner with drug designers to turn target-specific questions into tractable ML problems, driving innovation in AI/ML approaches to undruggable targets and data-poor target spacesMentor scientists and contribute to the scientific direction and technical strategy for our in silico platform and AI capabilitiesUphold reproducibility and experimental rigor through experiment tracking, model versioning, code review, testing, and documentationStay current with the literature and publish or present work where appropriateRequired QualificationsPhD in Computational Chemistry, Chemical Engineering, Chemistry, Computer Science with chemistry focus, or related field, or equivalent industry experience4+ years of professional experience developing and deploying machine learning models in production environmentsExpert-level Python programming with demonstrated ability to build complex scientific software systemsExpertise in deep learning and experience designing and training multiple types of neural network architectures (CNNs, RNNs, Transformers, Diffusion models, GANs, etc.) Please note that a high degree of depth in any single type of architectures is required, and having familiarity with every single architecture listed is not strictly necessary.Proven experience with large-scale model training on GPU clusters, including projects requiring weeks to months of continuous training timeExperience with distributed training across multiple GPUs and optimization of training pipelines for computational efficiencyStrong computational chemistry background with hands-on experience running and analyzing physics-based simulations such as molecular dynamics, Monte Carlo methods, or quantum chemical calculations. As with the deep learning architectures, a high degree of familiarity with at least one of these types of simulations is required.Deep understanding of cheminformatics principles and practical experience with molecular data processing, including molecular file formats, molecular descriptors, fingerprints, and substructure searchingProficiency with modern deep learning frameworks (PyTorch, TensorFlow, JAX)Experience with molecular representation learning and applying ML to chemical/biological problemsStrong knowledge of 3D molecular structures, protein-ligand interactions, and structure-based drug design principlesProven track record of delivering complex ML projects from research through production deploymentExcellent communication skills with demonstrated ability to effectively collaborate with chemists, engineers, and drug designersAbility to translate scientific requirements into technical specificationsPassion for solving seemingly impossible problems and pushing the boundaries of what's possibleStrong problem-solving skills and ability to work at the intersection of chemistry, physics, and machine learningPreferred QualificationsExperience with reinforcement learning for molecular design or optimizationSpecific expertise with any of the following: transformer architectures, large language models, or diffusion modelsExperience with generative AI for chemistry and molecular designKnowledge of equivariant neural networks or geometric deep learning for molecular systemsExperience analyzing molecular dynamics trajectories and identifying key collective variablesKnowledge of uncertainty quantification in ML models for chemistryBackground in quantum chemistry calculations and their integration with ML workflowsExperience with computational chemistry software packages (Gromacs, AMBER, OpenMM, PSI4, ORCA, Gaussian, etc.)Hands-on experience with cheminformatics libraries (RDKit, Open Babel, CDK) and molecular property prediction toolsExperience with protein-ligand docking, virtual screening, or ADMET predictionExperience with automated machine learning (AutoML) or hyperparameter optimization for molecular modelsPublications in computational chemistry, machine learning for drug discovery, or AI/ML conferencesFamiliarity with experiment tracking and model management tools (MLflow, Weights & Biases, etc.)Experience with cloud computing platforms (AWS, GCP, Azure) for large-scale ML trainingTechnical SkillsPython for scientific computingDeep learning frameworks (PyTorch, TensorFlow, JAX)Large-scale and multi-GPU model trainingCheminformatics libraries (RDKit, Open Babel)Molecular simulation packages (Gromacs, AMBER, OpenMM, or similar)High-performance computing and SLURM or similar job schedulersScientific computing libraries (NumPy, SciPy, scikit-learn, pandas)Version control systems (Git)Experiment tracking and model management toolsMolecular visualization tools (PyMOL, VMD, or similar)Dataset curation and preparation for large-scale molecular dataLinux/Unix environments and bash scriptingWhat We OfferOpportunity to work on previously undruggable targets and fundamentally change the paradigm of drug discoveryCollaborative environment with world-class scientists, engineers, drug hunters, and quantum chemistsCompetitive compensation package including equity and an annual bonusComprehensive health, life, short- and long-term disability insurance policies401K matchingAccess to cutting-edge computational resources and our proprietary BEYOND platform24/7 access to a world-class fitness centerProfessional development and mentoring opportunitiesTen63 Therapeutics is an equal opportunity employer. We embrace diversity and are committed towards inclusion. xhyhwjd We encourage applications from all qualified candidates regardless of race, color, religion, sex, national origin, age, disability, or any other protected characteristic.

Job Tags

Similar Jobs