Senior Machine Learning Engineer

A NASDAQ-listed company that is committed to making heart disease prevention and early diagnosis more accessible, individualized, and accurate, is looking for a Senior Machine Learning Engineer. The engineer will be in charge of organizing and leading technical teams for various modeling projects. The company is revolutionizing the healthcare industry with their innovative cardiovascular care solutions that combine modern epigenetics, genetics, and AI technology. The company has managed to successfully secure $11mn+ in funding so far. 

Job Responsibilities:

• 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