Full-Stack Software Developer AI/ML Platform
| Company | Autodesk |
|---|---|
| Location | Montreal, QC, Canada, Toronto, ON, Canada, Vancouver, BC, Canada |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Mid Level, Senior |
Requirements
- BS in Computer Science, or equivalent practical experience
- Over 3 years of experience in front-end software development
- Strong knowledge of HTML, CSS, and JavaScript is essential
- Experience with one or more modern front-end frameworks or libraries such as React, Angular, Vue.js, or Svelte
- Ability to integrate RESTful services or GraphQL APIs
- Proficiency in using version control systems, especially Git
- Experience with front-end testing frameworks and libraries (e.g., Jest, Mocha, Jasmine) and debugging tools (e.g., Chrome DevTools)
- Familiarity with design and prototyping tools such as Adobe XD, Sketch, Figma, or InVision
- Ability to work closely with UX designers, back-end developers, and data scientists
- Experience working in an Agile development environment, familiar with Scrum or Kanban, and using project management tools like Jira
Responsibilities
- Develop and maintain full-stack applications that power internal AI/ML workflows, including user-friendly front-end interfaces (React, Angular, or Vue) and robust back-end services (Node.js, Python, Java, etc.)
- Implement scalable APIs and microservices to handle large volumes of data and interact seamlessly with data pipelines, model-training systems, and analytics dashboards
- Collaborate with data scientists and DevOps teams to integrate ML models into production environments, ensuring reliable deployment, monitoring, and CI/CD processes
- Optimize performance and security of AI/ML platforms by implementing best practices for data handling, authentication, authorization, and application monitoring
- Contribute to platform architecture and technical strategy, working cross-functionally to define requirements, evaluate new technologies, and drive continuous improvements across the stack
Preferred Qualifications
- While not mandatory, having a basic understanding of AI and ML concepts can be beneficial
- Have a portfolio showcasing your previous designs with real users
- AWS, GCP, Azure deployment patterns, with Microservice architecture on Kubernetes preferred
- Understanding of web performance optimization techniques and tools. Knowledge of how to improve page load times and end-user experience by optimizing assets, code splitting, lazy loading, etc.