MLOps Engineer
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- North Vancouver, BC
- 100.000-150.000 $ par an
- Permanent
- Temps-plein
- Build ML Platforms: Design and maintain the cloud-based infrastructure (AWS) that supports scalable model training and batch inference pipelines.
- Automate the Lifecycle: Develop and manage CI/CD pipelines for machine learning, ensuring that model training, testing, and deployment are automated and reproducible.
- Model Operations: Implement best practices for model versioning, registry management, and artifact tracking. You will ensure that every model in production is traceable and secure.
- Reliability & Monitoring: Proactively manage system health by implementing monitoring and logging tools. You will lead incident responses for the ML stack and ensure high availability for data processing workflows.
- Bachelor's degree in Computer Science, Engineering, or a related field.
- 3+ years of professional experience in a DevOps, MLOps, or Software Engineering role.
- Proficiency in Python and experience with automation scripting.
- Experience with cloud infrastructure, specifically AWS (SageMaker, Batch, Lambda, S3).
- Proficiency with containerization and orchestration tools (Docker, Kubernetes).
- Experience building CI/CD pipelines for software or machine learning projects.
- Experience with workflow orchestration tools (e.g., Prefect, Airflow, Kubeflow).
- Experience with Infrastructure as Code (IaC) tools like Terraform and Ansible.
- Familiarity with MLOps tools for experiment tracking (e.g., Weights & Biases, DVC, MLFlow).
- Knowledge of model optimization techniques (quantization, pruning) for deployment.
- Understanding of security best practices in a cloud environment.
- Strong communication skills and ability to work in a team.
eQuest