Senior Machine Learning Operations Engineer - AI/ML Platform

• 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 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

• Security and Compliance:

Enforce security best practices and compliance standards in all aspects of

MLOps

, ensuring 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:

Play a key role in

identifying

and resolving 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 DevOps and

MLOps

, with a focus on deploying and managing machine learning models in production environments

• Infrastructure as Code (IaC

):

Proficiency

in implementing Infrastructure as Code practices using tools such as Terraform or Ansible

• Containerization:

Strong

expertise

in containerization technologies (Docker, Kubernetes) for orchestrating and scaling machine learning workloads

• CI/CD:

Demonstrated

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

• Scripting and Automation:

Strong scripting skills in Python, Bash, or similar languages for automating operational processes

• Monitoring Tools:

Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack) for tracking system and model performance

• Security Awareness:

Understanding of

security best practices in

MLOps

, including data encryption, access controls, and compliance standards

• Collaboration Skills:

Excellent collaboration and communication skills, working effectively with cross-functional teams including data engineers, software developers, and researchers

• Problem-solving Skills:

Proven ability to troubleshoot and resolve complex operational issues

in a timely manner

Preferred Qualifications

• Cloud Experience:

Experience with cloud platforms, especially AWS or Azure, for deploying and managing machine learning infrastructure

• Database Knowledge:

Familiarity with databases and data storage solutions commonly used in

MLOps

, such as SQL, NoSQL, or data lakes

• Machine Learning Frameworks:

Exposure to popular machine learning frameworks (TensorFlow,

PyTorch

) and their integration into

MLOps

processes

• Collaboration Tools:

Previous

experience with collaboration tools like Git for version control and Jira for project management

• Agile Methodology:

Familiarity with Agile development methodologies and working in an iterative, collaborative environment

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About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Salary transparency

Salary is one part of Autodesk’s competitive compensation package. For Canada-BC based roles, we expect a starting base salary between $123,000 and $180,400. 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.

Diversity & Belonging

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