Machine Learning Scientist

About the Role:As one of the first ML-focused scientists in this stealth start-up company, you will lead the integration of machine learning into our R&D processes. You will collaborate closely with our interdisciplinary team of wet- and dry-lab scientists and engineers to implement state-of-the-art ML algorithms. Your role will be to advance our computational biology capabilities, design experiments, and help optimize our genome modification technologies. You will utilize both proprietary and public datasets to build scalable models, ultimately enabling our novel CRISPR-Cas platform to address unmet medical needs.Working with a diverse team of protein and RNA engineers, computational scientists, cell biologists and molecular biologists, and translational scientists, you will:Develop and deploy machine learning algorithms to support human therapeutic development, with a focus on protein and gRNA engineering in CRISPR-Cas systemsLead the design and implementation of machine learning pipelines using in-house and public datasets, including genomic, proteomic, and functional experimental dataCollaborate with wet- and dry-lab scientists to couple data-analysis to the subsequent experimental designs that will test and validate specific mechanistic or therapeutic hypothesesInnovate methods to optimize the design of CRISPR guide RNAs (gRNAs) and proteins in complex with genomic targets, balancing efficacy and safety in therapeutic contextsExplore and implement cutting-edge algorithms to engineer novel genome modification modalities, including predictive modeling, active learning, and generative designWork cross-functionally to align machine learning efforts with company goals in research and therapeutic developmentDevelop rigorous tools and frameworks to facilitate large-scale data analysis and experiment designStay up-to-date with the latest advancements in ML, computational biology, and genome modification to ensure our approaches remain state-of-the-artMentor colleagues across the organization, fostering a culture of machine learning excellenceRequirements

:Ph.D. or M.S. in Computer Science, Machine Learning, Bioinformatics, Computational Biology, or a related field, or equivalent industry experience5+ years of hands-on experience in machine learning, ideally within the biotechnology, pharmaceutical, or computational biology sectorsDeep understanding of ML algorithms, including supervised and unsupervised learning, active learning, language models, and foundational modelsExperience applying ML techniques to problems in protein design, genomics, or CRISPR technologiesProficiency in programming languages such as Python, R, or C++, and machine learning libraries such as TensorFlow, PyTorch, or Scikit-learnStrong experience with data wrangling and analysis in large-scale biological datasets (e.g., genomic, proteomic, RNA-seq)Experience utilizing high performance compute (HPC) environments to create scalable ML infrastructure.Familiarity with CRISPR-Cas systems and gene editing technologies is highly desirableExcellent communication skills, with the ability to collaborate effectively in a multidisciplinary team settingPreferred Qualifications:Experience with experimental design and high-throughput screening workflowsExperience with fine-tuning foundational models in genomics, proteomics, or structure prediction Familiarity with tools such as MPNN, ESMFold, AlphaFold, and similarExperience working in a startup environment and thriving in a fast-paced, innovative atmosphere Engineering interests in genetic disease, immunology, or neurology