Senior Fullstack Software Engineer

Autodesk Autodesk · Enterprise · EMEA - United Kingdom - London - Agar St

Senior Fullstack Software Engineer to support research and foundation model development. The role involves building systems for rapid experimentation, prototyping, model deployment, evaluation, and integration into production workflows, working closely with research scientists, ML engineers, and infrastructure teams. The engineer will also work with 3D data and contribute to CI/CD and data pipelines.

What you'd actually do

  1. Develop and maintain backend and frontend applications and services
  2. Rapidly prototype solutions to support research and experimentation workflows
  3. Design, implement, and monitor CI/CD systems and deployment pipelines
  4. Build tooling for benchmarking, evaluation, and post-training workflows (e.g., harnesses, environments)
  5. Work with 3D data (meshes/BREPs) and support 3D geometry processing and rendering systems

Skills

Required

  • Strong programming skills in Python (or similar)
  • Experience developing full stack applications (backend + frontend)
  • Experience using modern AI/GenAI tools as part of the development workflow
  • Familiarity with cloud infrastructure (e.g., AWS), Linux environments, and containerization (Docker)
  • Experience with CI/CD tools and workflows
  • Experience building or working with data pipelines
  • Ability to work in fast-paced, ambiguous environments and drive tasks to clarity
  • Bachelor's degree in computer science, Engineering, or equivalent experience
  • Strong problem-solving, communication, and collaboration skills

Nice to have

  • Experience building prototypes in research or experimental settings
  • Familiarity with workflow/pipeline orchestration tools (e.g., Metaflow)
  • Experience working with 3D data, CAD systems, or rendering techniques
  • Experience with frontend technologies (e.g., JavaScript, React)
  • Understanding of software architecture and design patterns
  • Ability to work across multiple domains (systems, data, UI) as needed
  • Interest in machine learning or AI systems
  • Experience supporting or deploying experimental ML models (evaluation, iteration, or internal use)
  • Strong experience with Ray (data, training, or serving use cases)
  • Familiarity with DevOps practices and tools (e.g., Kubernetes, Terraform)
  • Exposure to 3D modelling software and file formats (e.g., meshes, BREPs)
  • Proficiency in a low-level programming language (e.g., C, C++, Rust)
  • Experience with other cloud platforms (Azure, GCP)

What the JD emphasized

  • high-ambiguity environment
  • requirements are often not fully defined
  • evolving or unclear requirements

Other signals

  • supporting research and foundation model development
  • enabling rapid experimentation, prototyping, and model deployment
  • building systems that support model development, evaluation, and integration into production workflows
  • collaborate with research scientists, ML engineers, and infrastructure teams to enable AI/ML solutions