Machine Learning Engineer

• work with a team of scientists tasked with identifying, developing, and deploying data-rich technologies aimed at improving the manner in which process understanding is gathered
• leverage fundamental process modeling, machine learning, and other innovative data science approaches to enable our process research and development efforts across our Company's biologics and vaccines portfolio
• embed data-intense technologies into the fabric of our Company’s process development culture
• solve complex process research and development challenges in an interdisciplinary, collaborative environment via invention, development, and application of cutting-edge process modeling including novel deep neural network architectures and their combination with physics and theory through hybrid methods
• combine process modeling and deep learning techniques to help advance process-focused scientific research
• develop mechanistic, hybrid, or data-driven models for chemical synthesis and isolation, cell culture, fermentation, biomolecule separations
• work closely alongside pipeline project teams to extract impactful insights from experimental data for manufacturing process design
• employ process models to accelerate and enhance laboratory development through ML-assisted optimal experiment design
• apply physics-based and hybrid models to guide and de-risk scale-up/scale-down during technology transfer and commercialization
• develop new hybrid machine learning frameworks based on customized deep learning architectures and their integration with physics-based models or structures
• collaborate with enterprise IT colleagues for the automated scaling, training, and serving of such models to an extensive process development organization.

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