DevOps Engineer

at  Quarterhill

Overview:
The DevOps Engineer will enhance our development and delivery infrastructure with a focus on supporting both traditional software development and machine learning workflows. This includes building, deploying, and maintaining CI/CD pipelines, with a particular emphasis on integrating and supporting machine learning operations (MLOps) for scalable and secure ML pipelines. The role will also focus on ensuring model development adheres to best practices like versioning, auditability, and data security.

Responsibilities:

• Design, implement, and manage robust CI/CD pipelines to facilitate seamless code integration and deployment, and machine learning (ML) model releases.
• Develop and maintain automated solutions for infrastructure provisioning and management, and machine learning pipelines, ensuring consistency and scalability, and model versioning.
• Monitor system performance, identify and resolve issues promptly, and ensure the availability and reliability of development and production environments for both Software and ML model environments.
• Implement and manage security practices within the CI/CD pipelines and infrastructure to protect against vulnerabilities and ensure compliance with industry standards.
• Continuously improve the performance of the infrastructure and CI/CD processes, and ML pipelines by identifying bottlenecks and implementing solutions for optimization.
• Integrate various DevOps tools and ML frameworks (e.g., TensorFlow, PyTorch) to create a cohesive, efficient development, and machine learning environment.
• Support model development, focusing on auditability, versioning, and scalability for machine learning models.
• Partner closely with development, AI/ML and QA teams to ensure the smooth and timely integration and delivery of software products.
• Apply software engineering rigor and best practices to machine learning systems, ensuring effective automation and orchestration.
• Create and maintain comprehensive documentation for DevOps processes, tools, ML pipelines, and configurations to ensure transparency and knowledge sharing.

This list of responsibilities might not cover everything you’ll end up doing.

Qualifications:

• Bachelor’s degree in Computer Science, Computer Engineering, or a related field.
• 1-3 years of experience in a DevOps role or similar position.
• Proficiency with CI/CD tools (e.g., Jenkins, Bitbucket, CircleCI) and infrastructure as code (e.g., Terraform, Ansible).
• Experience with MLOps and developing ML pipelines, including model training, validation, and deployment.
• Experience developing and maintaining machine learning systems built with open-source tools (e.g., TensorFlow, PyTorch, MLflow).
• Basic scripting skills in Python, Bash, or similar languages.

Benefits:

We offer a Total Rewards plan designed with you and your family’s health and wellness in mind that includes:

• Paid days off (i.e. vacation, sick days, bereavement leave)
• Health and Dental plans
• Retirement plans
• Employee and Family Assistance Program (EFAP)
• Employee referral program

We welcome applicants from all backgrounds, regardless of race, color, religion, sex, veteran status, sexual orientation, gender identity, national origin, age, or disability or any other protected characteristics in accordance with applicable federal, state/provincial, and local laws. We’re committed to creating a workplace where everyone feels valued and respected.
We appreciate all responses and will acknowledge only those being considered for an interview.
We respectfully request no calls or unsolicited resumes from Agencies

• Design, implement, and manage robust CI/CD pipelines to facilitate seamless code integration and deployment, and machine learning (ML) model releases.
• Develop and maintain automated solutions for infrastructure provisioning and management, and machine learning pipelines, ensuring consistency and scalability, and model versioning.
• Monitor system performance, identify and resolve issues promptly, and ensure the availability and reliability of development and production environments for both Software and ML model environments.
• Implement and manage security practices within the CI/CD pipelines and infrastructure to protect against vulnerabilities and ensure compliance with industry standards.
• Continuously improve the performance of the infrastructure and CI/CD processes, and ML pipelines by identifying bottlenecks and implementing solutions for optimization.
• Integrate various DevOps tools and ML frameworks (e.g., TensorFlow, PyTorch) to create a cohesive, efficient development, and machine learning environment.
• Support model development, focusing on auditability, versioning, and scalability for machine learning models.
• Partner closely with development, AI/ML and QA teams to ensure the smooth and timely integration and delivery of software products.
• Apply software engineering rigor and best practices to machine learning systems, ensuring effective automation and orchestration.
• Create and maintain comprehensive documentation for DevOps processes, tools, ML pipelines, and configurations to ensure transparency and knowledge sharing