Machine Learning Engineer (Senior/ Staff)
Toronto, Ontario /
Predictive Systems /
Deep Genomics is a startup company that aims to revolutionize drug development by leveraging expertise in artificial intelligence (AI) to decode RNA biology. Our proprietary platform, the AI Workbench, enables us to decode the enormous complexity of RNA biology to find novel targets, mechanisms, and molecules that are not accessible through traditional methods. We use this advanced technology to develop steric-blocking oligonucleotides (SBOs) that achieve expression increase for the treatment of genetic disease. Founded in 2015, our multidisciplinary team includes expertise in a diverse range of disciplines including those found in a traditional drug company, as well as machine learning, laboratory automation, and software engineering. Deep Genomics is based in Toronto, Ontario with additional locations in Cambridge, Massachusetts and Montreal, Quebec.
Where You Fit In
As an ML Engineer you will be a part of the core ML group responsible for developing the models that power our AI workbench. You will be responsible for designing, developing, and deploying machine learning models as well as the software infrastructure for rapid and reproducible model development.
What you will do:
- Work with our ML scientists to develop models and algorithms using state-of-the-art neural network methodologies.
- Develop evaluation, visualization, and productivity tools for streamlining machine learning research.
- Adapt our algorithms and architectures to best exploit modern cloud computing environments (GPUs/TPUs)
- Keep up-to-date with the latest ML research and techniques, and apply them to our solutions.
- Mentor and guide junior machine learning engineers.
What you bring:
- Solid Engineering and Computer Science fundamentals, ideally with a degree in CS, Math, or equivalent experience.
- 5+ years of professional experience as a software developer/engineer
- Experience in architecting, developing, and deploying large software systems in a leading position
- Expertise with implementation details of large neural-network architectures such as Transformers with frameworks like PyTorch, Tensorflow, Keras, JAX, etc.
- Experience with CloudML and MLOps tools (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning).
- Excellent communication skills and the ability to work in a team environment.
Nice to have:
- Experience within the biotechnology or healthcare space.
What we offer:
- A highly competitive salary and meaningful equity compensation (ESOPs)
- A wide array of company-paid benefits
- Exceptional opportunities for learning and growth working alongside a world-class team of researchers and software developers 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