Day Zero Diagnostics (DZD) is an infectious disease diagnostics company using whole genome sequencing and machine learning to combat the rise of antibiotic-resistant infections. We are developing a product that will allow microbiology labs to perform comprehensive bacterial species identification and and genomic antibiotic resistance profiling within 8 hours of receiving a sample, all without the need for time-consuming blood cultures. Providing this information in hours rather than days would enable faster appropriate antibiotic therapy for systemic infections such as sepsis, reduce hospital treatment durations, and reduce treatment costs.

At DZD we are passionate about our mission of modernizing infection disease diagnosis and treatment. Employees gain experience in a multidisciplinary and fast-paced start-up and have ample opportunities to acquire new skills, engage with emerging technologies, work closely with our accomplished team, and communicate their results, all while working in a supportive and energetic environment. We work in state-of-the-art facilities within an exceptional research setting.

This Machine Learning Scientist position is on the data science team at DZD, which is responsible for training machine learning models to predict antimicrobial resistance from genomic sequencing data and generally supporting data analytics across the company. The Machine Learning Scientist can expect to be involved in the planning and execution of model R&D (featurization, model specification and training, performance analysis, etc), as well as ad hoc analytics work and preparing models for deployment into production. As an experienced researcher, the team will rely on your ability to take broad questions and turn them into actionable research programs and search the literature for appropriate approaches. Much of the work will involve interactions with our software engineering and computational biology teams, and being able to work both collaboratively and independently are key.

Primary responsibilities:

  • Develop, improve, and maintain code for feature set creation, model training, and performance analysis for relevant machine learning tasks
  • Build statistical and analytical tools to support machine learning models and general analytical needs across the company
  • Search the scientific literature for solutions to research questions and adapt the state of the art to the problem at hand
  • Provide expertise in machine learning and statistical analysis best practices
  • Maintain organized, tested code and corresponding documentation
  • Present data and results to internal stakeholders and outside of the company at meetings/conferences/etc
  • Write, edit, and submit manuscripts/abstracts/grants detailing the results of research projects
  • Work closely within the data science team and with outside collaborators
  • Maintain close communication with the team regarding progress


  • PhD in computer science, machine learning, computational biology, or an equivalent quantitative field.
  • Fluency in in Python, SQL, and Linux
  • Dedication to coding best practices
  • Mastery of statistical/machine learning foundations and best practices
  • Fluency with the Python data science and machine learning ecosystem: NumPy, PyPlot, scikit-learn, TensorFlow/PyTorch, etc.
  • Familiarity with biological sequencing data analysis helpful, but not required
  • Enthusiasm for learning about and solving problems in a new field
  • Highly motivated and independent, with the ability to in a dynamic team environment
  • Strong oral and written communication skills