Uncubed
   

Machine Learning Engineer (All levels)

Deep Genomics, Toronto/Boston/San Francisco Bay Area/Remote North America Only

Creating A New Universe Of Genetic Medicines

Duration: Full-Time


About Us
Founded in 2015, Deep Genomics is a drug development company that aims to revolutionize medicine by leveraging expertise in artificial intelligence (AI) and genome biology. We have built the world’s first, and by far the most advanced, AI platform that is able to untangle the enormous complexity of RNA biology and find the best targets, mechanisms, and molecules.   

The thesis here at Deep Genomics is that everyone, at some point in their life, will face a genetic condition, whether Mendelian or complex, and we aim to be there for them with a genetically precise therapy. We take immense pride in our team of people whose backgrounds span a diverse range of disciplines including those found in a traditional biotechnology company, as well as machine learning, laboratory automation, and software engineering.   

Ideal Candidate
Our predictive systems group brings together world-leading experts in biology, genomics, medicine, and machine learning. We are working on several ambitious projects to develop pioneering AI technology for understanding complex genetic diseases and enabling the discovery of novel targets as well as therapies. We are looking for an experienced machine learning engineer to lead the design and development of new models and pipelines and the infrastructure for scaling it up to the next level.

What You’ll Be Doing:

  • Working with our ML scientists to develop highly scalable models and algorithms for predicting molecular phenotypes using state-of-the-art neural network methodologies.
  • Developing evaluation, visualization, and productivity tools for streamlining machine learning research 
  • Adapting our algorithms and architectures to best exploit modern cloud computing environments
  • Working with our software engineers, biologists and geneticists to operationalize and deploy research output to match the needs of stakeholders.

What You Bring:

  • Solid Engineering and Computer Science fundamentals, ideally with a degree in CS, Math, or equivalent experience.
  • Senior candidates should have experience in architecting, developing, and deploying large software systems in a leading position
  • Experience in building, testing, training, and deploying production-ready ML workflows. 
  • Experience developing machine learning algorithms or machine learning infrastructure in Python or C/C++.
  • Experience with frameworks like PyTorch, Caffe2, Tensorflow, Keras, JAX, Chainer, etc.
  • Experience in the operationalization of Machine Learning projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning).

What we offer:

  • Leading role in developing the future of drug development to cure genetically defined diseases. 
  • A highly competitive salary and meaningful equity compensation.
  • Exceptional opportunities for learning and growth.
  • A bright, collegial, highly motivated team working at the intersection of the most exciting areas of science and technology.
Deep Genomics thanks all applicants, however only those selected for an interview will be contacted. 

Deep Genomics welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.

About Deep Genomics

Deep Genomics is using artificial intelligence to build a new universe of life-saving genetic therapies. The future of medicine will rely on artificial intelligence, because biology is too complex for humans to understand. At Deep Genomics, our geneticists, molecular biologists and chemists develop new ways of detecting and treating disease using our biologically accurate artificial intelligence technology.

Deep Genomics

Want to learn more about Deep Genomics? Visit Deep Genomics's website.