Senior Software Engineer (Full Stack)
Deep Genomics
Key Responsibilities
- Design and implement full stack internal web applications deployed to the cloud (we use GCP).
- Design and implement Python libraries, APIs, SDKs, and CLI tools to enable and accelerate our R&D efforts.
- Implement robust integrations with 3rd party platforms such as Benchling and Weights & Biases.
- Mentor junior engineers with a mindset of elevating the team as a whole.
- Collaborate closely with product managers, scientists, and engineers to build innovative products that enable and accelerate drug development, and unlock new opportunities.
Basic Qualifications
- 5+ years of professional experience as a software developer/engineer.
- Strong proficiency in React and Python.
- Extensive experience in developing and designing end-to-end web applications with modern frontend frameworks, server-side frameworks with cloud/microservices deployments, and SQL/NoSQL databases.
- Intimate knowledge of the entire software engineering process from design, to implementation, documentation, testing, deployment, and maintenance.
Preferred Qualifications
- Understanding of UX design principles with experience in designing simple and intuitive user interfaces.
- Knowledge of DevOps, CI/CD, and security in cloud environments.
- Familiarity with ML model development processes and tooling.
- Experience working with genomic data (our scientists also enjoy helping with impromptu lessons).
What we offer
- A collaborative and innovative environment at the frontier of computational biology, machine learning, and drug discovery.
- Highly competitive compensation, including meaningful stock ownership.
- Comprehensive benefits - including health, vision, and dental coverage for employees and families, employee and family assistance program.
- Flexible work environment - including flexible hours, extended long weekends, holiday shutdown, unlimited personal days.
- Maternity and parental leave top-up coverage, as well as new parent paid time off.
- Focus on learning and growth for all employees - learning and development budget & lunch and learns.
- Facilities located in the heart of Toronto - the epicenter of machine learning and AI research and development, and in Kendall Square, Cambridge, Mass. - a global center of biotechnology and life sciences.
