Full-Stack Software Developer AI/ML Platform

Job Requisition ID #

25WD87568

About Autodesk
Autodesk makes software for people who make things. We are a global leader in 3D design, engineering, manufacturing, and entertainment software. Our customers use Autodesk software to design and make the physical and virtual worlds that we live in. If you've ever driven a high-performance car, admired a towering skyscraper, used a smartphone, or watched a great film or played an immersive game, chances are you've experienced what millions of Autodesk customers are doing with our software.

Position Overview
We are seeking a dynamic and enthusiastic full-stack software engineer to develop our next-generation AI/ML platform used in the development of Autodesk’s suite of products and services. Join our dynamic and rapidly expanding team to help build innovative capabilities that enable faster and more secure development of machine learning and generative AI solutions, bolstering the intelligence of Autodesk software products and services. You will collaborate with research and product engineering from various domains including design, construction, manufacturing, and media & entertainment to deliver the platform that supports the full AI/ML development lifecycle.

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

Minimum Qualifications

• Education : BS in Computer Science, or equivalent practical experience
• Experience : Over 3 years of experience in front-end software development
• Proficient in Front-End Technologies : Strong knowledge of HTML, CSS, and JavaScript is essential. The candidate should be able to create responsive, accessible, and cross-browser compatible UIs
• Frameworks and Libraries : Experience with one or more modern front-end frameworks or libraries such as React, Angular, Vue.js, or Svelte. Knowledge of state management libraries (e.g., Redux, Vuex) is also beneficial
• API Integration : Ability to integrate RESTful services or GraphQL APIs, understanding of asynchronous request handling, partial page updates, and AJAX
• Version Control Systems : Proficiency in using version control systems, especially Git, for code management and collaboration
• Testing and Debugging : Experience with front-end testing frameworks and libraries (e.g., Jest, Mocha, Jasmine) and debugging tools (e.g., Chrome DevTools)
• Design and Prototyping Tools : Familiarity with design and prototyping tools such as Adobe XD, Sketch, Figma, or InVision to translate design concepts into functional UI components
• Collaboration and Communication : Ability to work closely with UX designers, back-end developers, and data scientists to ensure the UI meets the functional and aesthetic needs of the AI/ML platform
• Agile Methodologies : Experience working in an Agile development environment, familiar with Scrum or Kanban, and using project management tools like Jira

Preferred Qualifications

• Understanding of AI/ML Concepts : While not mandatory, having a basic understanding of AI and ML concepts can be beneficial to better align the UI with the platform's functionality and user requirements
• UX/UI and taste: Have a portfolio showcasing your previous designs with real users
• Public Cloud Experience: AWS, GCP, Azure deployment patterns, with Microservice architecture on Kubernetes preferred
• Web Performance Optimization : 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.