5 days ago
Toronto, Canada or Montréal, CanadaMid Level
Responsibilities
- Design, build, test, deploy, and operate reliable services and production data pipelines.
- Develop end-to-end information extraction solutions involving classification, OCR, document-layout processing, model-based extraction, refinement, and validation.
- Take LLM- and machine-learning-backed features from prototype to production using cloud model providers while balancing quality, latency, reliability, and cost.
- Design and own distributed system components including queue-based pipelines, fan-out and fan-in workflows, backpressure, idempotency, retries, failure handling, and data-loss safeguards.
- Diagnose distributed pipeline issues using structured logs, custom metrics, and traceable queries.
- Build and maintain React applications and shared component libraries with TypeScript in a monorepo.
- Develop Terraform infrastructure as code and operate AWS networking, load balancing, API gateways, encryption, IAM, and logging and metrics pipelines.
- Design CI/CD workflows, tune containerized services, and share knowledge with interns, data scientists, and software developers.
Requirements
- Bachelor’s degree in computer science, software engineering, or equivalent education and experience.
- Proficiency with Python, REST or GraphQL APIs, and AWS services including S3, Lambda, and SageMaker or similar services.
- Experience with machine learning and scientific computing libraries such as scikit-learn, NumPy, SciPy, and TensorFlow.
- Experience with pipelines, ingestions, or automations.
- Knowledge of software engineering practices, development cycles, Git, Jira, and Confluence.
- Ability to work collaboratively, communicate effectively, manage time and organization, and address vaguely defined issues creatively.
- Motivation to learn AI is acceptable in place of prior AI experience.
- Candidates must be eligible to work in Canada; Quebec-based candidates must be bilingual because of regular interaction with English-speaking colleagues across Canada.
- Nice-to-have experience includes dependency manager, CI platform, or infrastructure migrations; emulated-cloud development and integration-test harnesses; container tuning; Kubernetes and ELK; MongoDB or Kafka; advanced document processing; production data and machine-learning pipelines; and insurance-domain experience.
Benefits
- Flexible work arrangements and a hybrid work model.
- Possibility to purchase up to five additional days off per year.
- Physical and mental wellbeing benefits including telemedicine and a wellness account.
- Share plan, savings opportunities, annual bonus plan, employee share purchase plan with 50% matching of net shares, and defined benefit pension plan.
- No Canadian work experience is required, but candidates must be eligible to work in Canada from the anticipated start date and throughout employment.
Tech Stack
Apache KafkaAWSGitGraphQLKubernetesMongoDBNumPyPythonReactscikit-learnSciPyTensorFlowTerraformTypeScript
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