MLOps Engineer, Fusion Team. Canada

24WD76061

Position Overview

The Fusion Machine Learning team is a multi-disciplinary team of engineers and researchers developing AI/ML solutions to some of the biggest problems in 3D design, manufacturing, and mechanical engineering. We are seeking an MLOps/DevOps engineer who is passionate about transforming scaling mature production-ready AI powered applications through optimizing the underlying infrastructure.

You will collaborate with researchers and engineers to continuously improve the data, train and release pipelines by automating repositories to ensure quality and interoperability with deploy systems and upgrading prototype code to run on large cloud-based ML Learning training infrastructure.

You will report to the Fusion Platform ML manager and play a critical role in the Autodesk AI strategy.

You will report to the Sr. Manager, Software Development for ML Research.

Location: The role is located in Canada.

Responsibilities

• Operational Efficiency: Improve the team's efficiency by implementing MLOps and DevOps practices

• Deployment Automation: Adapt research models to automated deployment pipelines

• Scalable Development: Collaborate with engineers and researchers to ensure research code can transition to training and inference at scale

• Monitoring and Logging: Track model performance, system health, and overall platform efficiency

• Version Control and Model Governance: Mature single-version codebases to iterable, pipeline-deployed and version-controlled solutions

• Security, Compliance and Governance: Contribute to the implementation of model governance practices, and enforce company-wide security best practices and compliance standards in all aspects of DevOps and MLOps

• Continuous Improvement: Identify opportunities for process automation, optimization, and implement strategies to enhance the MLOps lifecycle

• Troubleshooting and Incident Response: Help resolve operational issues, contributing to incident response and system recovery

Minimum Qualifications

• Educational Background: BS in Computer Science or related field, or equivalent experience

• Cloud Experience: Experience with cloud platforms, such as AWS or Azure, for deploying and managing machine learning infrastructure

• MLOps / DevOps Experience: 3-5 years of hands-on experience in MLOps / DevOps in a production environment

• Infrastructure as Code (IaC): Proficiency in implementing Infrastructure as Code practices using tools such as Terraform

• Containerization: Expertise in containerization technologies (Docker, Kubernetes) for orchestrating and scaling machine learning applications

• CI/CD: Demonstrated experience setting up and managing Continuous Integration and Continuous Deployment (CI/CD) pipelines for machine learning projects

• Scripting and Automation: Scripting skills in Python, Bash, or similar languages for automating operational processes

• Security Awareness: Understanding of security best practices in MLOps, including data encryption, access controls, and compliance standards

​Preferred Qualifications:

• Machine Learning Frameworks: Exposure to popular machine learning frameworks (TensorFlow, PyTorch) and their integration into MLOps processes

• Monitoring Tools: Familiarity / experience with monitoring and logging tools (e.g., Prometheus, Grafana, or ELK Stack) for tracking model and system performance

• Agile Methodology: Familiarity / experience with Agile development methodologies and working in an iterative, collaborative environment

• Database Knowledge: Familiarity / experience with databases and data storage solutions commonly used in MLOps, such as SQL, NoSQL, or data lakes

• Repository and Pipeline Technologies: Familiarity / experience with Git, Jenkins, and YAML

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Salary is one part of Autodesk’s competitive compensation package. For Canada-BC based roles, we expect a starting base salary between $78,200 and $156,200. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, we also have a significant emphasis on annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

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