Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
The ideal candidate has experience putting industrial-scale Machine Learning Models into production, understands the needs of Data Scientists, is familiar with the biomedical domain, and is eager to apply his or her skills to improve patient outcomes.
What You Will Do:
- Build and deploy robust, industrial scale Machine Learning and Data Pipelines for structured and unstructured data
- Facilitate End-to-end large scale machine learning model integration
- Collaborate with product, science, engineering, and business development teams to build the most advanced data solutions in precision medicine
- Proficient in Python.
- Experience working in GCP, AWS, and other Cloud Environments.
- Knowledge of best practices for code development, documentation, testing and deployment patterns.
- Experience building and maintaining robust, large-scale Machine Learning and Data Pipeline designed for scalability, repeatability, automation, CI/CD/CT, performance monitoring, model dashboarding.
- Strong programming skills, familiarity with software development cycles, solid understanding of software concepts - data structures and algorithms.
- Experience with deployment of Natural Language Processing models.
- Experience with elastic search, knowledge graph.
- Experimental management and logging frameworks (e.g. MLflow), data and pipeline versioning.
- Experience with ML model testing: model performance, model health, etc.
- Good familiarity with deep learning frameworks: PyTorch, TensorFlow, Keras.
- Good familiarly Data Engineering & Architecture best practices.
- Biomedical domain expertise.