Character Biosciences is a precision medicine platform company focused on treating diseases of aging with the highest unmet needs. Character Biosciences is building the world’s largest integrated clinical genomic databases in priority areas of unmet need through partnerships with patients, healthcare providers, payers, academic medical centers, and other industry and non-profit partners. The company combines genetics, clinical and imaging data, computational biology, machine learning, and novel experimental approaches to deconvolute complex genetically associated diseases of aging. This technology significantly bolsters the probability of success and efficiency of drug development by redefining diseases at the molecular level and precisely targeting treatments for each patient cohort. Character has raised funding through an elite group of investors at the convergence of technology and drug discovery.
The candidate would be integral to a growing data science and engineering team reporting to the VP of Data Science. The candidate will lead workflows involving machine learning, especially computer vision tasks, to generate robust disease phenotypes from clinical imaging data. This position offers a unique opportunity to join early in a dynamic and growing company. The role also allows for tremendous growth opportunities as the company expands.
As a Machine Learning Engineer, you will:
Lead the development of new machine learning, primarily computer vision, and causal inference models and methods to classify and predict disease progression, treatment response, and health outcomes using longitudinal imaging and clinical data (e.g., EMR, insurance claims).
Work with various biomedical imaging types across disease modalities, volumetric and non-volumetric image data.
Lead the development and analyses to normalize and integrate heterogeneous datasets.
Identify and lead innovative technical developments in data sciences methodologies, workflows, and applications. Collaborate with the broader science teams on novel machine learning approaches to streamline and improve the entire drug discovery and development process.
Transform large & diverse incoming data-streams to reproducible machine learning workflows
Position minimum requirements:
Bachelor’s or foreign equivalent in Computer Science, Information Technology, Software Engineering, or related field
5+ years of experience in the job offered or related occupation in Machine Learning, Computer Vision, and/or Pattern Recognition
Strong knowledge of Python and deep learning platforms (e.g., PyTorch)
Deep knowledge and experience in development of traditional machine learning architectures (e.g., SVM, Random Forest) and deep learning (e.g., CNNs, Transformers, GANs) approaches and frameworks
Expert in computer vision and image processing tasks (e.g., segmentation, classification, Optical character recognition)
Ability to setup and work with the Python data science stack: pandas, numpy, PIL, scikit-learn, scipy and familiarity with tabular data
In depth understanding of fundamental computer vision algorithms and optimization strategies
Can debug, fine-tune, modify, and maintain pipelines based on imperfect data (i.e., missing time points, data composition differences)
Experience working in cloud computing environments and infrastructure (e.g., Google Cloud)
Experience with reproducible workflows and version control
Experience with database creation and management (e.g., postgres)
Results-oriented; ownership and accountability; self-directed
Highly collaborative; respectful of and skilled at leveraging others’ expertise
Exceptional communication skills, both written and verbal
U.S work eligibility
Position preferred qualifications:
Advanced degree: Master’s/Doctorate in Computer Science, Information Technology, Software Engineering, or related field
Experience working in the life sciences, preferably with clinical imaging and Electronic Health Record data.
Experience in both research and production environments
Experience with visualization techniques and dashboard platforms
Demonstrated leadership and self-direction. Demonstrated willingness to teach others and learn new techniques.
Tagged as: Computer Science, Engineering, Life Sciences
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