Senior Machine Learning Operations Developer: AI/ML Platform (Toronto)

Position Overview
Autodesk, a global leader in 3D design, engineering, manufacturing, and entertainment software, is seeking a skilled MLOps Engineer 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 support platform operations. Responsibilities
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 engineers to ensure efficient data pipelines for model training and validation. Implement version control systems for machine learning models and contribute to model governance practices. Enforce security best practices and compliance standards in all aspects of MLOps. Identify opportunities for process automation, optimization, and implement strategies to enhance the overall MLOps lifecycle. Identify and resolve operational issues, contributing to incident response and system recovery. Qualifications
Minimum Qualifications
BS or MS in Computer Science, or related field. 5+ years of hands‑on experience in DevOps and MLOps, focusing on deploying and managing machine learning models in production environments. Proficiency in implementing Infrastructure as Code (IaC) using Terraform or Ansible. Strong expertise in containerization technologies (Docker, Kubernetes) for orchestrating and scaling machine learning workloads. Demonstrated experience setting up and managing CI/CD pipelines for machine learning projects. Strong scripting skills in Python, Bash, or similar languages for automating operational processes. Familiarity with monitoring tools such as Prometheus, Grafana, and the ELK Stack for tracking system and model performance. Understanding 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. 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. Knowledge of Agile development methodologies and iterative, collaborative working environments. Salary and Benefits
Salary is one part of Autodesk's competitive compensation package. For Canada based roles, we expect a starting base salary between $0 and $0. Offers are based on the candidate's experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.
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