Senior Machine Learning Operations Developer – AI/ML Platform

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 ensures the smooth operationalization of machine learning models and the overall efficiency of our next‑generation AI/ML platform that powers Autodesk’s suite of products and services.

You will collaborate with research and product engineering teams across design, construction, manufacturing, and media & entertainment to support platform operations.

Responsibilities

• Operational Efficiency: Drive the operational excellence of our AI/ML Platform by implementing and optimizing MLOps practices.
• Deployment Automation: Design and implement automated deployment pipelines for machine learning models, ensuring seamless transitions from development to production.
• Scalable Infrastructure: Collaborate with cross‑functional teams to design, implement, and maintain scalable infrastructure for model training, inference, and data processing.
• Monitoring and Logging: Develop and maintain robust monitoring and logging systems to track model performance, system health, and overall platform efficiency.
• Collaboration with Data Engineers: Work closely with data engineers to ensure efficient data pipelines for model training and validation.
• Version Control and Model Governance: Implement version control systems for machine learning models and contribute to model governance practices.
• Governance and Trust: Contribute to robust model governance practices, compliance standards, data privacy, and ethical considerations.
• Security and Compliance: Enforce security best practices and compliance standards to ensure data privacy and platform security.
• Continuous Improvement: Identify opportunities for process automation, optimization, and implement strategies to enhance the overall MLOps lifecycle.
• Troubleshooting and Incident Response: Identify and resolve operational issues, contributing to incident response and system recovery.
• Minimum Qualifications
• Educational Background: BS or MS in Computer Science or related field.
• MLOps Experience: 5+ years of hands‑on experience in Dev Ops and MLOps, focusing on deploying and managing machine learning models in production environments.
• Infrastructure as Code: Proficiency in implementing Ia C practices using Terraform or Ansible.
• Containerization: Strong expertise in Docker and Kubernetes for orchestrating and scaling machine learning workloads.
• CI/CD: Experience setting up and managing CI/CD pipelines for machine learning projects.
• Scripting and Automation: Strong scripting skills in Python or Bash for automating operational processes.
• Monitoring Tools: Familiarity with Prometheus, Grafana, ELK Stack for tracking system and model performance.
• Security Awareness: Understanding of security best practices in MLOps, including encryption, access controls, and compliance.
• Collaboration Skills: Excellent collaboration and communication skills, working effectively with cross‑functional teams.
• Problem‑Solving Skills: Proven ability to troubleshoot and resolve complex operational issues promptly.
• Preferred Qualifications
• Cloud Experience: Experience deploying and managing machine learning infrastructure on AWS or Azure.
• Database Knowledge: Familiarity with SQL, No SQL, or data lake solutions commonly used in MLOps.
• Machine Learning Frameworks: Exposure to Tensor Flow or Py Torch and integration into MLOps processes.
• Collaboration Tools: Experience with Git for version control and Jira for project management.
• Agile Methodology: Familiarity with Agile development methodologies.
• Salary Transparency

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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