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 Pipelines for Natural Language Processing
- 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
- BS/MS/PhD in a quantitative or computational field such as Computer Science, Computer Engineering, Machine Learning or related field and 2+ (for MS) or 5+ (for BS) years of industry/academic experience.
- Experience building and maintaining robust, large-scale Machine Learning Pipeline designed for portability, composability, scalability, repeatability, automation, CI/CD/CT, performance monitoring, model dashboarding.
- Experience working in GCP, AWS, and other Cloud Environments.
- Experience with Kubernetes (e.g. GKE, EKS).
- Experience with Kubeflow.
- Experience with ML model testing: model performance, model health, etc.
- Knowledge of best practices for code development, documentation, testing and deployment patterns.
- Proficient in Python.
- Strong programming skills, familiarity with software development cycles, solid understanding of software concepts - data structures and algorithms.
- Thrive in a fast-paced environment and willing to shift priorities seamlessly.
- Team player mindset and ability to work in an interdisciplinary team.
- Goal orientation, self motivation, and drive to make a positive impact in healthcare.
- Experience with deployment of Natural Language Processing models.
- Experimental management and logging frameworks (e.g. MLflow), data and pipeline versioning.
- Good familiarity with deep learning frameworks: PyTorch, TensorFlow, Keras.
- Biomedical domain expertise.