Senior Full Stack Engineer
$200k - $250k per yeararcadia
Location: Toronto | 3 days/week in officeType: Full-time | PermanentCompensation: $200-250K CAD base + equity + benefits + 4 weeks’ vacationAn 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 visualizationDevelop features across React, Python/Node.Js, GraphQL, and PostgreSQLDesign, deploy, and scale ML inference services using Kubernetes and Ray ServeOwn cloud infrastructure and deployment workflows using Terraform, Terragrunt, and ArgoCDBuild CI/CD pipelines that help researchers deploy models efficiently and reliablyDevelop pipelines for ingesting, processing, and moving large‑scale medical imaging datasetsCollaborate with product teams and stakeholders to shape requirements and technical directionWhat We’re Looking For
5+ years of software engineering experience building and operating production applicationsStrong full‑stack skills across frontend development, backend services, and database designHands‑on experience designing and operating production workloads on KubernetesStrong infrastructure‑as‑code experience with Terraform and familiarity with GitOpsExperience with AWS, Docker, and modern CI/CD workflowsPractical experience using AI coding agents on existing codebases, with sound judgment around testing and reviewStrong communication skills and the ability to take ownership in a fast‑moving teamNice to Have
Experience with ML inference, computer vision, or production model‑serving systemsFamiliarity with Ray Serve, Ray Data, or Ray TrainExperience with medical imaging, DICOM, or clinical data pipelinesExposure to multi‑cloud environments or HPC tools such as SlurmExperience in healthcare or regulated environmentsExperience building custom agentic tooling, such as MCP servers, skills, or hooksWhy Join
Build technology with a direct impact on cancer research and clinical trialsOwn meaningful work across both the software product and ML infrastructureHelp shape engineering practices within an AI‑native team
#J-18808-Ljbffr
Build applications for clinical data acquisition, management, and visualizationDevelop features across React, Python/Node.Js, GraphQL, and PostgreSQLDesign, deploy, and scale ML inference services using Kubernetes and Ray ServeOwn cloud infrastructure and deployment workflows using Terraform, Terragrunt, and ArgoCDBuild CI/CD pipelines that help researchers deploy models efficiently and reliablyDevelop pipelines for ingesting, processing, and moving large‑scale medical imaging datasetsCollaborate with product teams and stakeholders to shape requirements and technical directionWhat We’re Looking For
5+ years of software engineering experience building and operating production applicationsStrong full‑stack skills across frontend development, backend services, and database designHands‑on experience designing and operating production workloads on KubernetesStrong infrastructure‑as‑code experience with Terraform and familiarity with GitOpsExperience with AWS, Docker, and modern CI/CD workflowsPractical experience using AI coding agents on existing codebases, with sound judgment around testing and reviewStrong communication skills and the ability to take ownership in a fast‑moving teamNice to Have
Experience with ML inference, computer vision, or production model‑serving systemsFamiliarity with Ray Serve, Ray Data, or Ray TrainExperience with medical imaging, DICOM, or clinical data pipelinesExposure to multi‑cloud environments or HPC tools such as SlurmExperience in healthcare or regulated environmentsExperience building custom agentic tooling, such as MCP servers, skills, or hooksWhy Join
Build technology with a direct impact on cancer research and clinical trialsOwn meaningful work across both the software product and ML infrastructureHelp shape engineering practices within an AI‑native team
#J-18808-Ljbffr
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