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Software Engineer, Machine Learning

Passionate about making a difference in the world of cancer genomics?

With the advent of genomic sequencing, we can finally measure and process our genetic makeup. We now have more data than ever before but providers often don't have the infrastructure or expertise required to easily extract the valuable insights that exist in said data. Here at Tempus, we believe the greatest promise for the detection and treatment of cancer lies in building a deep understanding of the interaction between molecular activity and clinical treatment, through the discovery of response patterns and unique biomarkers.

We're on a mission to connect an entire ecosystem to redefine how genomic data is used in clinical settings. We are looking for machine learning engineers who are passionate and excited by the prospect of building the most advanced data platform in cancer care.

What You'll Do

  • Work with our data science and user interface teams to build our data visualization and analysis tools and algorithms
  • Coordinate with our various engineering and science teams to bring together the numerous sources of data inside Tempus
  • Become proficient in our data and engineering infrastructure components and champion their continuous improvement


  • Degree in computer science, software engineering or related technical field
  • Proficient in Python
  • Experience working in a Linux / Mac environment
  • Experience with the following: Git, SQL, Pandas, NumPy, SciPy, Scikit-learn, Jupyter Notebooks
  • Familiarity with: matplotlib, seaborn, HTML5, CSS3, JavaScript, D3,, Flask, NodeJS, ReactJS
  • Experience with the structure and usage of REST API's
  • Outstanding programming and problem solving skills
  • Self-driven and work well in an interdisciplinary team with minimal direction
  • A strong desire to understand why things work the way they do
  • Thrive in a fast-paced environment and willing to shift priorities seamlessly
  • Excellent communication skills

Nice to Haves

  • Experience building and validating predictive models on structured or unstructured data
  • Experience working with clinical and/or genomic data
  • Experience in agile environments and comfort with quick iterations
  • Experience with AWS architecture
  • Experience in Big Data technologies such as Spark, Hadoop
  • Experience in High-scale web applications and architecture
  • Experience with continuous integration infrastructure for software development such as Jenkins, CircleCI, etc.
  • Experience in Docker
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