Autodesk currently has 101 active job listings related to AI. The majority of these roles, 59%, are focused on agents, with application and serving infrastructure also representing significant portions. Engineering is the dominant function for these hires, with Canada and the United States being the top hiring countries. Frequent technical tags include agent orchestration, LLM observability, model serving, RAG, and tool use.
Currently tracking 59 active AI roles, down 55% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $131k–$323k (avg $211k).
Autodesk currently has 107 active AI-related roles in our index. The most common open titles are: Principal Software Engineer (3), Principal Data Scientist (2), Principal Software Development Engineer (2), Senior Software AI Developer (2), Software Architect (2). Most positions are in Engineering and Product.
Autodesk's active AI hiring is concentrated in: agents (54%), serving infrastructure (15%), application (12%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Autodesk is hiring AI talent in: Canada (48 roles), United States (25 roles), India (12 roles), United Kingdom (4 roles).
Job postings at Autodesk most frequently reference: agent orchestration, llm observability, model serving, rag, evals.
In the past 30 days, Autodesk has posted 34 new AI-related roles. That is a -56% change versus the prior 30 days (78 → 34).
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Engineering Manager, Model Delivery Machine Learning Engineering Manager on the Model Delivery team within Autodesk Research, leading production ML engineering across deployment, monitoring, evaluation, reliability, and operational excellence for ML-powered features. This role involves leading and growing a team of ML engineers, improving models based on production issues and feedback, leading production release processes, building observability and on-call practices, developing evaluation frameworks, and leading reliability/performance/cost improvements for inference and serving. The role also partners with researchers, product, and platform teams to define quality bars and production readiness, including Trusted AI requirements, and establishes production standards for ML features. | ShipServe | 8 |