Senior Machine Learning Operations Developer, Inference, AI/ML Platform

Job Requisition ID # 26WD94525 L'affichage de poste en français suivra / The French job posting follows. 26WD94525 Senior Machine Learning Operations Developer, Inference, AI/ML Platform Position Overview Autodesk, a global leader in 3D design, engineering, manufacturing, and entertainment software, is seeking a skilled  Senior MLOps  Developer to join our AI/ML Platform team. This role is pivotal in ensuring the smooth operationalization of machine learning models and the overall efficiency of our   next-generation AI/ML platform used in the development of machine learning and generative AI solutions powering Autodesk’s suite of products and services. You will collaborate with research and product engineering from various domains including design, construction, manufacturing, and media &   entertainment to   to   support platform operations.

Drive the operational excellence of our AI/ML Platform by implementing and   optimizing   MLOps   practices Design and implement automated deployment pipelines for machine learning models, ensuring seamless transitions from development to production Collaborate with cross-functional teams to design, implement, and   maintain   scalable infrastructure for model training, inference, and data processing Develop and   maintain   robust monitoring and logging systems to track model performance, system health, and overall platform efficiency Work closely with data developers to ensure efficient data pipelines for model training and validation Implement version control systems for machine learning models and contribute to model governance practices Contribute to the implementation of robust model governance practices, version control systems, and adherence to compliance standards. Uphold data privacy and ethical considerations, fostering trust in our AI/ML solutions Enforce security best practices and compliance standards in all aspects of   MLOps , ensuring data privacy and platform securit Identify   opportunities for process automation, optimization, and implement strategies to enhance the overall   MLOps   lifecycle Play a key role in   identifying   and resolving operational issues, contributing to incident response and system recovery   Minimum Qualifications BS or MS in Computer Science, or related field 5+ years of hands-on experience in DevOps and   MLOps , with a focus on deploying and managing machine learning models in production environments Proficiency   in implementing Infrastructure as Code practices using tools such as Terraform or Ansible Strong   expertise   in containerization technologies (Docker, Kubernetes) for orchestrating and scaling machine learning workloads Demonstrated   experience in setting up and managing Continuous Integration and Continuous Deployment (CI/CD) pipelines for machine learning projects Strong scripting skills in Python, Bash, or similar languages for automating operational processes Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack) for tracking system and model performance U nderstanding of   security best practices in   MLOps , including data encryption, access controls, and compliance standards Excellent collaboration and communication skills, working effectively with cross-functional teams including data developers, software developers, and researchers Proven ability to troubleshoot and resolve complex operational issues   in a timely manner   Preferred Qualifications Experience with cloud platforms, especially AWS or Azure, for deploying and managing machine learning infrastructure Familiarity with databases and data storage solutions commonly used in   MLOps , such as SQL, NoSQL, or data lakes Exposure to popular machine learning frameworks (TensorFlow,   PyTorch ) and their integration into   MLOps   processes Previous   experience with collaboration tools like Git for version control and Jira for project management Familiarity with Agile