(Senior) Machine Learning Scientist, Oligonucleotides

(Senior) Machine Learning Scientist, Oligonucleotides THE OPPORTUNITY Machine learning lies at the core of insitro's approach to rethinking drug development. We've built a TherML https://www.insitro.com/news/introducing-insitros-therml-rapidly-engineering-the-right-therapeutic-for-the-right-target/ Platform that uses AI to accelerate pan-modality therapeutic discovery from hit-finding through lead optimization. Our innovative approach enables us to rapidly design therapeutics against internally discovered novel targets, with models powered by some of the industry's largest and most comprehensive datasets. We're looking for a Machine Learning Scientist who will be hands-on using our TherML platform to drive design on multiple oligonucleotide therapeutic programs while directly contributing to the development of our platform and ML models. This role offers an opportunity to translate cutting-edge ML into real-world impact on drug discovery. This role will report to the Senior Manager, Molecular Machine Learning and is a flexible hybrid (2 days per week in office) or remote (1 week per quarter on-site) role. RESPONSIBILITIES Develop insitro’s TherML Platform: - Work with industry-leading knockdown and off-target datasets to train and finetune foundation nucleotide models - Develop oligonucleotide generative AI methods for on-target knockdown and off-target gene misregulation - Collaborate with our computational chemists to apply MD simulation and other in-silico modeling based approaches to optimize oligonucleotide design based on RNA-protein interactions - Collaborate with software engineering teams to build robust pipelines for active/iterative learning and automated DMTL cycles - Directly shape the roadmap for our TherML platform's evolution Integrate AI to Drive Our Oligonucleotide Discovery Programs: - Collaborate cross-functionally with machine learning scientists and oligonucleotide scientists to design and prioritize novel compounds using model outputs - Apply predictive models and AI-enabled design methods to solve real molecular optimization challenges across multiple therapeutic programs - Track performance of our on-target knockdown and off-target models on discovery programs and translate those insights into model improvements - Communicate model capabilities, results, limitations, and recommendations clearly to diverse stakeholders in regular discovery team meetings ABOUT YOU - PhD in computational biology, computer science, machine learning, cheminformatics, or related field - 0-3+ years of industry experience applying machine learning to oligonucleotide therapeutic discovery - Strong programming skills in Python and modern deep learning frameworks (PyTorch or TensorFlow) - Demonstrated expertise in developing deep learning and/or generative AI methods for RNA and/or DNA - Understanding of RNA structure, siRNA/ASO mechanism of action, and mRNA design - Proficiency with genomic sequence analysis across species - Excellent communication skills with ability to translate technical concepts to diverse audiences - Familiarity with oligonucleotide therapeutics discovery process and design methods COMPENSATION & BENEFITS AT INSITRO Our target starting salary for successful US-based applicants for this role is $185,000 - $235,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data. This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies. In addition, insitro also provides our employees: - 401(k) plan with employer matching for contributions - Excellent medical, dental, and vision coverage as well as mental health and well-bei ... (truncated, view full listing at source)