About
Mirai Bio, Inc is a Flagship backed biotechnology company focused on transforming information molecule therapeutics. The role involves designing, implementing, and deploying novel machine learning approaches to optimize therapeutic delivery vehicles and collaborating with cross-functional teams to develop computational tools for genomic medicines.
Responsibilities : • Design, build, and deploy production-grade ML models for optimization of lipid nanoparticle (LNP) formulation, synthesis, and in vivo performance. • Develop and implement scalable software best practices for uncertainty quantification, ensuring models are reliable for real-time decision-making. • Engineer robust data pipelines to integrate multi-fidelity datasets (in silico and in vivo) to accelerate data-driven discovery of novel LNPs • Collaborate with computational scientists to translate research models into maintainable, efficient software that identifies design pathways for LNPs that achieve targeted functional properties • Work with infrastructure and automation teams to architect and streamline real-time data transfer between predictive models and experimental platforms • Partner with experimental teams to drive iterative design–make–test–analyze (DMTA) cycles • Communicate findings to stakeholders and leadership through written reports and technical presentations.
Qualifications : Required : • PhD or Masters in Computer Science, Applied Mathematics, Bioengineering, Chemical Engineering, or a related quantitative field with a strong ML and Software Engineering focus. • 4+ years of experience developing and deploying ML models in a production environment within industry and/or academic settings. • Strong experience with uncertainty quantification, active learning, and Bayesian Optimization in drug delivery, materials science, or related fields. • Proficiency in ML frameworks (PyTorch/TensorFlow/JAX) and the Python data science ecosystem. • Demonstrated experience with MLOps principles (version control, CI/CD, monitoring) and hands-on experience with cloud computing infrastructure (e.g., AWS, GCP, Azure) to accelerate model training, deployment, and inference. • Strong independent problem-solving ability and attention to detail. • Demonstrated achievement in industry or academia (publications, patents, or successful ML system deployments). • Excellent communication and presentation skills for both technical and interdisciplinary audiences. • Enthusiasm for working with cross-functional teams of experimentalists, engineers, and computational scientists in a fast-paced, entrepreneurial environment.
Preferred : • Hands-on experience building and managing ML packages. • Experience with ML experiment tracking platforms (e.g. MLflow, Weights & Biases) • Familiarity with API development and microservices for integrating ML models into experimental workflows. • Background in drug delivery, lipid chemistry, or nanoparticle formulation.
Company :
Flagship Pioneering is a venture capital firm that invests in life sciences and healthcare companies. Founded in 2000, the company is headquartered in Cambridge, USA, with a team of 501-1000 employees. The company is currently Late Stage.
Languages
- English
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