Senior Full Stack Engineer

Location: Toronto | 3 days/week in office

Type: Full-time | Permanent

Compensation: $200-250K CAD base + equity + benefits + 4 weeks’ vacation

An AI company focused on medical imaging and clinical research is hiring a Senior Full Stack Engineer to build software that helps bring effective cancer treatments to patients sooner.

The team develops AI models that use medical imaging to predict patient outcomes and help global pharmaceutical companies make better decisions throughout clinical trials.

This is a hands‑on role spanning product development and ML infrastructure. You’ll own key parts of a clinical annotation and data platform, alongside the production systems that deploy and serve imaging models. There’s significant scope to build from the ground up, influence technical decisions, and work closely with researchers and product stakeholders.

What You’ll Do

• Build applications for clinical data acquisition, management, and visualization
• Develop features across React, Python/Node.js, GraphQL, and PostgreSQL
• Design, deploy, and scale ML inference services using Kubernetes and Ray Serve
• Own cloud infrastructure and deployment workflows using Terraform, Terragrunt, and ArgoCD
• Build CI/CD pipelines that help researchers deploy models efficiently and reliably
• Develop pipelines for ingesting, processing, and moving large‑scale medical imaging datasets
• Collaborate with product teams and stakeholders to shape requirements and technical direction

What We’re Looking For

• 5+ years of software engineering experience building and operating production applications
• Strong full‑stack skills across frontend development, backend services, and database design
• Hands‑on experience designing and operating production workloads on Kubernetes
• Strong infrastructure‑as‑code experience with Terraform and familiarity with GitOps
• Experience with AWS, Docker, and modern CI/CD workflows
• Practical experience using AI coding agents on existing codebases, with sound judgment around testing and review
• Strong communication skills and the ability to take ownership in a fast‑moving team

Nice to Have

• Experience with ML inference, computer vision, or production model‑serving systems
• Familiarity with Ray Serve, Ray Data, or Ray Train
• Experience with medical imaging, DICOM, or clinical data pipelines
• Exposure to multi‑cloud environments or HPC tools such as Slurm
• Experience in healthcare or regulated environments
• Experience building custom agentic tooling, such as MCP servers, skills, or hooks

Why Join

• Build technology with a direct impact on cancer research and clinical trials
• Own meaningful work across both the software product and ML infrastructure
• Help shape engineering practices within an AI‑native team