Machine Learning Engineer

The Genuity Artificial Intelligence Research Institute is seeking a highly motivated Machine Learning Engineer to help pioneer the use of generative and supervised AI/ML in the biomedical sciences. The candidate will work on establishing scalable AI/ML pipelines that will be used to analyze data generated from secondary/tertiary analysis to better understand disease etiology, identify novel drug targets, and discover biomarkers for use in precision medicine.

Given the multi-disciplinary nature of the position, strong collaboration and communication skills are expected.

Essential Qualifications

• M.Sc. in Engineering, Computational Statistics, Computer Science, Biostatistics, Bioinformatics, or related field with a minimum of 4-years of related industry and/or academic experience

• Experience in machine learning, deep learning, statistical methodology, predictive modeling and algorithm development

• Advanced programming skills with fluency in at least Python and/or R, with extensive experience using modern machine learning and deep learning libraries (TensorFlow, PyTorch, Edward, sklearn, caret, etc.)

• Comfortable within a Linux operating system and associated shell commands.

• Proven ability to design and code production grade machine AI/ML applications, along with a strong ability to visualize ‘big data’

• Ability to work on high-performance computing system and manage cloud computing environments (e.g. AWS) with experience working with GPUs

• Ability to address the requirements of the research team and develop new solutions, algorithms, and pipelines to facilitate discovery.

Preferred Qualifications:

• Ph.D. and postdoctoral training in Engineering, Computational Statistics, Computer Science, or another related field

• Understanding of modern genomics analysis including RNA-seq, single cell RNA-seq, DNA methylation, variant analysis, etc.

• Development and application of digital pathology and natural language processing algorithms

• Experience developing scalable production grade software.

• Up-to-date knowledge of the fast-moving AI/ML literature

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