Senior Machine Learning Engineer

• Analyze and combine extensive heterogeneous clinical and biological datasets to derive insights and stimulate new lines of inquiry
• Create a prototype of new analysis tools and algorithms for predicting patient outcomes and treatment responses using biomarkers
• Build the most cutting-edge data platform for precision medicine by working with the product, scientific, engineering, and business development teams
• Analysis should be scrutinized for robustness, validity, and out-of-sample stability
• Present your results to a group of stakeholders and colleagues after documenting and summarizing them

Job Requirements:

• Bachelor s/Master s/Ph.D. degree in Engineering, Computer Science, Biomedical Informatics, Machine Learning, Statistics, Computational Biology, Applied Mathematics, or Physics (or equivalent experience)
• At least 4+ years of relevant experience as a Machine Learning Engineer
• Extensive experience working with Python, Sklearn, and SQL
• Experience in self-supervised, supervised, and unsupervised Machine Learning methods, including regression, generative modeling, deep neural networks, gradient boosting, non-linear low dimensional embeddings, and clustering
• Extensive working knowledge of clinical and genetic data
• Ability to successfully explain complicated planning and technical information to stakeholders from a variety of backgrounds while maintaining strong programming abilities in a fast-paced, entrepreneurial setting
• Highly driven and self-directed person with a good work ethic
• Excellent analytical and problem-solving abilities, with a focus on comprehending the complexities of multi-modal medical data sets
• Familiarity working with cloud computing services like AWS is desirable
• Nice to have some experience developing machine learning-based models for cardiovascular outcomes
• Prior publications in peer-reviewed journals is desirable
• Fluent in written and spoken English communication skills