About Us
Deep Genomics is at the forefront of using artificial intelligence to transform drug discovery. Our proprietary AI platform decodes the complexity of genome biology to identify novel drug targets, mechanisms, and genetic medicines inaccessible through traditional methods. With expertise spanning machine learning, bioinformatics, data science, engineering, and drug development, our multidisciplinary team in Toronto and Cambridge, MA is revolutionizing how new medicines are created.
About the Role
As a Senior ML Engineer, you bring deep expertise in building robust production-grade machine learning systems and infrastructure. You’ll lead the design, development and maintenance of core components of our AI platform – spanning training pipelines, scalable inference, evaluation frameworks, experiment tracking and reproducible tooling. Collaborating closely with teams across engineering, machine learning, and biology, you’ll help push the boundaries of drug discovery through thoughtfully engineered systems.
Key ResponsibilitiesBuild and scale ML workflows: Collaborate closely with ML scientists and data scientists to design, implement and maintain reliable systems for model training, evaluation, and inference.Enable experiment tracking and reproducibility: Integrate model development workflows with tools such as Weights & Biases.Engineer robust data pipelines: Develop and maintain data ingestion and processing pipelines for scalability, reproducibility, reliability.Prototype and iterate quickly: Partner with stakeholders to rapidly develop proof-of-concepts.Promote software engineering best practices: Drive high standards in code quality, modular design, testing and CI/CD.Basic Qualifications3+ years of experience working as an ML Engineer, Software Engineer, or similar technical role focused on ML systems.Hands-on experience with ML frameworks, such as PyTorch, TensorFlow, or JAX.Proficient in Python, with a strong grasp of software architecture, design patterns, and a deep understanding of engineering best practices.Experience with containerization and orchestration tools, such as Docker and Kubernetes.Ability to mentor and elevate other team members' skills.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.
Deep Genomics thanks all applicants, however only those selected for an interview will be contacted.
