Machine Learning Operations Developer, AI/ML Platform

Autodesk

. Implement and optimize MLOps practices for Autodesk’s AI/ML Platform .

Posted 10/9/2026full-timeToronto • CanadaJuniorMid-Level💰 CA$99,000 - CA$145,200 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in MLOps practices, including the development and maintenance of automated deployment pipelines, scalable infrastructure, and monitoring systems for machine learning models. Proficient in implementing security best practices and compliance standards while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

MLOps ImplementationCI/CD Pipeline DevelopmentInfrastructure as CodeDocker and KubernetesPython Scripting

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

MLOpsCI/CDInfrastructure as CodePythonBashDockerKubernetesTerraformAnsibleModel Governance

Soft Skills

CollaborationCommunicationTroubleshootingProblem Solving

Tools & Technologies

PrometheusGrafanaELK StackAWSAzureGitJira

Industry Keywords

Data PrivacySecurity Best PracticesCompliance StandardsData EncryptionAccess Controls

Tech Stack

Tools & technologies

AnsibleAWSAzureDockerGrafanaKubernetesNoSQLPrometheusPythonPyTorchSQLTensorflowTerraform

About the role

Key responsibilities & impact

Implement and optimize MLOps practices for Autodesk’s AI/ML Platform
Develop and maintain automated deployment pipelines for machine learning models from development to production
Design, implement, and maintain scalable infrastructure for model training, inference, and data processing
Develop and maintain monitoring and logging systems for model performance, system health, and platform efficiency
Work with data developers to ensure efficient data pipelines for model training and validation
Implement model version control and contribute to model governance practices
Support data privacy, ethical considerations, security best practices, and compliance standards
Identify and implement process automation and optimization strategies across the MLOps lifecycle
Identify and resolve operational issues, contributing to incident response and system recovery
Collaborate with research, product engineering, data development, software development, and other cross-functional teams

Requirements

What you’ll need

BS or MS in Computer Science, or related field
2+ years of hands-on experience in DevOps and MLOps, focused on deploying and managing machine learning models in production environments
Experience with Infrastructure as Code using Terraform or Ansible
Experience with Docker and Kubernetes
Experience setting up and maintaining CI/CD pipelines for machine learning projects
Experience scripting in Python, Bash, or similar languages
Familiarity with Prometheus, Grafana, or ELK Stack
Understanding of security best practices, data encryption, access controls, and compliance standards
Excellent collaboration and communication skills
Ability to troubleshoot and resolve operational issues in a timely manner
Preferred: experience with AWS or Azure
Preferred: familiarity with SQL, NoSQL, or data lakes
Preferred: exposure to TensorFlow or PyTorch
Preferred: experience with Git and Jira
Preferred: familiarity with Agile development methodologies

Benefits

Comp & perks

Annual cash bonuses may be included
Commissions for sales roles may be included
Stock grants may be included
Comprehensive benefits package
In-person onboarding and/or in-person ID verification may be required