Machine Learning Engineer, Cell Imaging
Chicago, Illinois, United States
Applications have closed
Tempus
Tempus has built the world’s largest library of clinical & molecular data and an operating system to make that data accessible and useful, starting with cancer.Passionate about precision medicine and advancing the healthcare industry?
Passionate about building great software products that empower scientists and researchers?
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.
We are seeking a machine learning engineer to join our team. The ideal candidate has experience working with large imaging datasets, is familiar with the modern computer vision techniques and models, is familiar with the biomedical domain, and is eager to apply their skills to improve patient outcomes.
What you’ll do:
- Build and deploy robust, industrial scale machine learning models 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
- Research and develop next generation computer vision models to advance the state-of-the-art in high throughput microscopy.
Required Qualifications:
- BS or MS in computer science, biomedical engineering, or any quantitative field with a strong machine learning background.
- Breadth and depth knowledge of machine learning algorithms and best practices with an emphasis on computer vision models.
- Strong coding skills, Python preferred. Experience with version control (GIT) and collaborative software development and testing
- Experience working with Docker containers and cloud-based compute environments (e.g., AWS or GCP)
- Knowledge of best practices for code development, documentation, testing and deployment patterns.
- Strong team player and effective cross-team collaborator
Nice-to-haves:
- Experience with optical microscopy image analysis
- Experience building and deploying containerized applications and services
- Good familiarity with deep learning frameworks: PyTorch, TensorFlow, Keras.
- Previous experience in the healthcare sector
- Experience with Big Data technologies such as AWS, Hadoop, Spark etc.
Tags: AWS Big Data Computer Science Computer Vision Data pipelines Deep Learning Docker Engineering GCP Git Hadoop Industrial Keras Machine Learning ML models Pipelines Python PyTorch Research Spark TensorFlow Testing Unstructured data
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