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 |
|---|---|---|
| Principal Machine Learning Engineer Principal Machine Learning Engineer at Autodesk, focusing on integrating AI into AEC products. The role involves exploring and analyzing complex AEC datasets (BIM, drawings, point clouds), building and curating datasets for GenAI, prototyping workflows, and collaborating with AI researchers and product teams. The primary focus is on data preparation and understanding for AI applications within the AEC domain, with secondary involvement in model development and evaluation. | DataPost-train | 7 |
| Principal Research Engineer, AEC Data, Generative AI This Principal Research Engineer role focuses on building foundation models and generative AI tools for the AEC industry. The primary responsibilities involve developing scalable data pipelines for diverse AEC and infrastructure data sources, working with large-scale multi-modal datasets (text, geometric, terrain, reality capture) to design preprocessing and content understanding methods, and transforming unstructured data into representations suitable for machine learning. The role also involves collaborating with ML scientists to align data formats for downstream LLM training and fine-tuning, and applying data quality techniques. While the core is data engineering for ML (L0), there's a clear connection to downstream training and fine-tuning (L2). |
| DataPost-train |
| 7 |