Senior Machine Learning Engineer, Mlops

Senior Machine Learning Engineer Focused On Machine Learning Ops (Mlops) For Cad And Bim

The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world. As a Senior Machine Learning Engineer focused on Machine Learning Ops (MLOps) for CAD and BIM, you will ensure AI-powered experiences meet high standards for reliability, scalability, and operational excellence across Autodesk products. You will build and operate the infrastructure that takes models from development into production, including deployment automation, monitoring, and secure, scalable service integration. You will partner closely with researchers, evaluation engineers, and product teams to translate evaluation requirements into production quality gates, reduce operational risk, and continuously improve model performance in real customer environments. You will report to a manager in the Model Delivery team within Autodesk Research. This role is based in proximity to our North American west coast offices, including San Francisco, Portland, and Vancouver. We support both in-person, hybrid, and remote work.

Responsibilities:

• Test and Deploy Production Models: Automate model testing and validation. Implement and operate CI/CD pipelines to enable safe, repeatable deployments and rollbacks.
• Operate Inference Services: Provision and manage backend resources for inference (compute, containers, scaling), and tune performance, reliability, and cost in production.
• Monitor Model Health and Performance: Define and continuously monitor health and performance metrics for deployed services. Triage issues by severity and drive timely resolution, including incident response and runbooks.
• REST API Integration: Own end-to-end REST API integration, connecting backend model services to product and platform surfaces through scalable, containerized services.
• Product Ownership and Cross-functional Collaboration: Work with researchers, evaluation engineers, product managers, and partner engineering teams to deliver production-ready solutions, communicate status and risks, and escalate when needed.

Minimum Qualifications:

• BS or MS in Computer Science, Computer Engineering, or equivalent industry experience.
• 3+ years of professional software engineering experience building and operating production services.
• Experience automating testing and deployments using CI/CD, including release workflows that support safe rollouts and rollbacks.
• Experience building and operating cloud hosted, containerized services (for example Docker and Kubernetes or similar), including provisioning resources and scaling inference workloads.
• Experience building REST APIs using Python based frameworks (or similar), and integrating backend services with product or platform consumers.
• Strong software engineering fundamentals: version control, code quality, and writing maintainable, testable software.
• Strong written communication skills to document architectures, runbooks, and operational processes.

Preferred Qualifications:

• Experience running production ML or LLM inference services, including performance tuning, cost optimization, and capacity planning.
• Experience with observability tooling and practices (metrics, logging, tracing, alerting) and incident response in an on-call environment.
• Experience deploying services within an enterprise internal platform environment with standardized pipelines, security controls, and compliance requirements.
• Familiarity with rate limiting, authentication and authorization, and API security best practices.
• Familiarity with design, manufacturing, or AEC workflows, and how backend services integrate into CAD/BIM product experiences.
• Familiarity with Agile or Scrum ways of working.