Senior Machine Learning Engineer

Job Requisition

We are looking to join our Growth Experience Technology Machine Learning Team (GET-ML)  team builds machine learning features that transform customer experience across Sales, Marketing, and Customer Success. Our current focus is a large‑language‑model driven conversational platform (Commerce and Support Assistant) that is live in production, and we are expanding into multi‑agent systems and intelligent automation.

As a Senior Machine Learning Engineer, you will design, develop, and evolve machine learning systems that support conversational AI, search, multi‑agent solutions, and intelligent automation on Autodesk’s customer platforms. You will work end to end—from data exploration and hypothesis formation through modeling, experimentation, deployment, and iteration on systems used by real customers. You will help shape technical direction, mentor teammates, and contribute to how we design, evaluate, and operate machine learning systems at scale.

• Design and implement machine learning capabilities that improve Autodesk’s customer‑facing platforms, including conversational question answering, search and retrieval, agent‑based workflows, and intelligent automation
• Train, adapt, and improve machine learning models, including classical ML models, deep learning models, and LLM‑based systems, for real‑world production use cases
• Perform statistical analysis and data exploration to generate datasets for model training, experimentation, and evaluation
• Translate business objectives and product requirements into problems that can be addressed using data, statistics, and machine learning
• Collaborate with other members of the team to reach better solutions, and to position our team at the cutting edge of technology and ML practice
• Work closely with engineers, MLOps, and product partners to deploy, monitor, and iterate on ML systems running at scale
• Provide technical leadership and mentorship to less experienced team members, supporting their growth and contributing to a strong team culture
• Contribute to improving evaluation practices, ML tooling, and the overall technical foundations of the team

• MS or PhD in Computer Science, Statistics, Engineering, Economics, or related field (non‑traditional ML backgrounds are welcomed)
• 3+ years of applicable work experience in ML
• Demonstrated experience applying machine learning techniques, including both classical ML and deep learning approaches, to real-world problems
• Proficiency with the Python machine learning stack, including Pandas, Num Py, and Scikit‑learn
• Experience with at least one deep learning framework, such as Py Torch
• Knowledge of experimental design and analysis, including evaluating model performance and interpreting results
• Experience or strong interest in NLP, information retrieval, conversational AI, or LLM‑based systems
• Ability to work effectively in cross-functional teams and collaborate with engineers, product partners, and other stakeholders
• Experience contributing to or supporting machine learning systems in production environments

• Experience working with Large Language Models, particularly in the context of RAG, conversational systems, question answering, or agent-based applications
• Exposure to fine‑tuning or adapting LLMs or embedding models for domain-specific use cases
• Experience with information retrieval, learning-to-rank, recommender systems, or other NLP-driven applications
• Familiarity with search technologies such as Open Search, Elasticsearch, Lucene, or Solr
• Experience with data pipelines, model serving, or MLOps practices, especially in cloud environments such as AWS
• Advanced software engineering skills, including data structures, algorithms, and building maintainable production code

There is no single ideal profile for this role. We encourage you to apply if you think you would add to our team’s ability to deliver innovative ML, even if you don’t meet every single criterion.

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