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 systems

• Lead the design and implementation of machine learning pipelines using in-house and public datasets, including genomic, proteomic, and functional experimental data

• Collaborate with wet- and dry-lab scientists to couple data-analysis to the subsequent experimental designs that will test and validate specific mechanistic or therapeutic hypotheses

• Innovate methods to optimize the design of CRISPR guide RNAs (gRNAs) and proteins in complex with genomic targets, balancing efficacy and safety in therapeutic contexts

• Explore and implement cutting-edge algorithms to engineer novel genome modification modalities, including predictive modeling, active learning, and generative design

• Work cross-functionally to align machine learning efforts with company goals in research and therapeutic development

• Develop rigorous tools and frameworks to facilitate large-scale data analysis and experiment design

• Stay up-to-date with the latest advancements in ML, computational biology, and genome modification to ensure our approaches remain state-of-the-art

• Mentor colleagues across the organization, fostering a culture of machine learning excellence

Requirements:

• Ph.D. or M.S. in Computer Science, Machine Learning, Bioinformatics, Computational Biology, or a related field, or equivalent industry experience

• 5+ years of hands-on experience in machine learning, ideally within the biotechnology, pharmaceutical, or computational biology sectors

• Deep understanding of ML algorithms, including supervised and unsupervised learning, active learning, language models, and foundational models

• Experience applying ML techniques to problems in protein design, genomics, or CRISPR technologies

• Proficiency in programming languages such as Python, R, or C++, and machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn

• Strong 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 desirable

• Excellent communication skills, with the ability to collaborate effectively in a multidisciplinary team setting

Preferred Qualifications:

• Experience with experimental design and high-throughput screening workflows

• Experience with fine-tuning foundational models in genomics, proteomics, or structure prediction • Familiarity with tools such as MPNN, ESMFold, AlphaFold, and similar

• Experience working in a startup environment and thriving in a fast-paced, innovative atmosphere • Engineering interests in genetic disease, immunology, or neurology

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