Automating and simplifying machine learning workflows and deployments
Implementing and delivering ML capabilities to solve complex real-world problems and deliver value
Design and implement streamlined end-to-end, continuous, and automated process of deploying, monitoring, and maintaining versioned ML models, at scale
Design and implement services, tests, and interfaces to support Machine Learning capabilities that improve Autodesk’s eCommerce & Customer platforms
Design and implement data pipelines and automated workflows to operationalize data at different stages of the Machine Learning lifecycle
Collaborate with other members of the team in reaching better solutions
Deploy innovative solutions from non-production environments to production with an eye on scalability and observability

BS or MS in Computer Science, Statistics, Engineering, Economics, or related field
0-3 years of applicable work experience in Software Engineering or Data Engineering or ML Engineering
Proficiency with the Python Machine Learning stack, e.g., Pandas
Demonstrate expertise with applying Machine Learning, specifically LLMs
Familiarity with Large Language Models, especially in the context of interactive dialog systems and chatbots (RAG, Generative AI, Conversational Agents)
Experience deploying systems that use NLP or experience working with Conversational AI frameworks
SQL and experience with big data technology such as Hive, Presto, Glue, (Py)Spark, or Athena
Experience with data pipelines and the AWS ML ecosystem
Strong Software Engineering skills

ML Ops Developer

Key skills