Design, build, and ship products and services that shape how pharma commercial teams engage with healthcare providers, working across the stack with product, design, and ML engineering.
Compensation
Final compensation is determined through a comprehensive review of the successful candidate’s unique skill set, specialized experience, certifications and other relevant considerations. As such, the final offer may vary based on these specific factors. Salary expectations will be discussed collaboratively early in the process to ensure alignment.
Responsibilities
Own significant product capabilities end-to-end, from ambiguous problem framing through design, implementation, deployment, and iteration with minimal oversight
Build accessible, data-rich user experiences with React and TypeScript
Build and maintain real-time computation services (AWS Lambda)
Design and maintain reliable, scalable APIs and backend services
Lead technical design, code review, and architectural discussions
As a Data Science Intern at Enveda, you will join our Data Science team and work on machine learning for mass spectrometry, computational biology, and computational chemistry.
Locations (2)
United States
Canada
Compensation
Compensation per month: US - Masters ($5000 USD), PhD ($6000 USD) & Canada - Masters or PhD ($8500 CAD)
Responsibilities
Learn how to develop data-driven solutions tailored to the drug discovery industry as part of our Data Science team
Collaborate on machine learning for mass spectrometry
Collaborate on computational biology and computational chemistry
Own significant product capabilities end-to-end, from ambiguous problem framing through design, implementation, deployment, and iteration with minimal oversight
Locations (4)
Vancouver, British Columbia, Canada
Toronto, Ontario, Canada
Canada
United States
Responsibilities
Own significant product capabilities end-to-end, from ambiguous problem framing through design, implementation, deployment, and iteration with minimal oversight
Build accessible, data-rich user experiences with React and TypeScript that make complex commercial and healthcare insights clear and actionable
Lead the design and architecture of complex, scalable software solutions, ensuring they are secure, highly available, fault tolerant, maintainable, and optimized for performance.
Compensation
For Canada-based remote roles, the expected base salary range for this position is CAD $140,000 to $170,000 annually.
Responsibilities
Lead the design and architecture of complex, scalable software solutions
Take ownership of high-impact projects from understanding the user's problem through design, implementation, deployment, and support in production
Mentor and provide guidance to associate engineers
Be a leader in how our teams use AI to deliver software
Work closely with product managers, designers, customers, and other teams to deliver software in small increments of business value
Requirements
Degree in Computer Science, Software Engineering, or a related field
Engineering Manager role to lead the team building, deploying, and customizing Spellbook for enterprise customers. A hybrid role of engineering manager and technical program lead.
Compensation
This role is not subject to Ontario's salary range disclosure requirement, as total compensation exceeds the threshold set out in the exemption.
Responsibilities
Own the Enterprise engineering plan
Partner with sales and the deal desk
Lead pre-sales prototyping
Lead, coach, and grow engineers across backend, full-stack, and forward-deployed roles
Drive delivery across teams
Requirements
Nice to have: enterprise SaaS deployments
Nice to have: integrations (DMS, CRM, procurement systems)
Nice to have: security and compliance (SOC 2, data residency)
Build and maintain real-time computation services (AWS Lambda) that serve scores and calculations on-demand to the customer-facing app, with an eye toward latency, reliability, and cost at scale
Design and maintain reliable, scalable APIs and backend services connecting ODAIA’s data, ML, analytics, and agentic capabilities to customer-facing products
Work across our stack: AWS, Kubernetes, Snowflake, PostgreSQL, and embedded analytical engines like DuckDB and DataFusion
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