Req Id: 428729 Connection is everything. It drives us to innovate, explore, and stay close to what matters to us most. At Bell, we’re building a more connected future through world-class networks, AI-powered solutions, and digital experiences that elevate how people live, work, and play every day. We believe in empowering people. That’s why we equip our teams with cutting-edge technology, AI tools, and a collaborative environment that supports creativity and growth. Want to be part of a diverse team where your work makes a real impact? If you’re inspired by innovation that advances how people connect and transforms what’s possible, you belong on #TeamBell. <div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px">Summary</H2> </div><div> As an Intermediate AI DevOps Engineer you are a skilled practitioner responsible for making the AI enablement vision a reality. This role involves supporting and executing within established frameworks to implement AI best practices, drive adoption, and ensure seamless AI integration across various business units (BUs).</div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px">Key Responsibilities</H2> </div><div> <ul> <li>AI Standardization & Adoption: Implement AI best practices and actively support their adoption across engineering teams.</li> <li>Cross-BU Collaboration: Work closely with different BUs' teams to ensure successful integration of AI capabilities and MLOps practices.</li> <li>MLOps Implementation & Configuration: Set up and configure MLOps tools, CI/CD pipelines, and infrastructure components according to established architectural designs.</li> <li>Developer Support: Directly assist development teams in utilizing enablement capabilities, troubleshooting pipeline issues, and providing guidance on best practices for AI/ML development.</li> <li>Documentation Contribution: Create and update user-facing documentation, tutorials, and examples for MLOps tools, processes, and AI enablement resources.</li> <li>Scripting & Automation: Develop scripts to automate routine tasks for both the enablement team and development teams, enhancing efficiency.</li> <li>Feedback Gathering: Systematically collect feedback from development teams regarding the usability and effectiveness of enablement resources and tools.</li> </ul></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px">Competencies</H2> </div><div> <ul> <li>MLOps Execution: Ability to implement and configure MLOps tools and CI/CD pipelines as designed.</li> <li>Technical Support: Skill in assisting developers, troubleshooting technical issues, and guiding them on best practices.</li> <li>Automation Development: Proficiency in scripting (e.g., Python, Bash) to automate routine tasks.</li> <li>Documentation: Capability to create and update clear, user-friendly technical documentation.</li> <li>Collaboration: Ability to work effectively with cross-functional teams and gather constructive feedback.</li> <li>Problem-Solving: Aptitude for identifying and resolving technical issues within established frameworks.</li> <li>·AI/ML Workflow Understanding: Foundational knowledge of AI/ML concepts and the importance of DevOps in their lifecycle</li> </ul></div></div><div style="padding:10.0px 0.0px;border:1.0px solid transparent"><div style="font-size:16.0px;word-wrap:break-word"><H2 style="font-size:1.0em;margin:0.0px">Critical Qualifications</H2> </div><div> <ul> <li>Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.</li> <li>2-4 years of experience in DevOps, SRE, or Software Engineering roles, with exposure to AI/ML development workflows.</li> <li>Hands-on experience configuring and managing CI/CD pipelines.</li> <li>Experience with scripting languages such as Python or Bash.</li> <li>Familiarity with cloud platforms (AWS, Azure, GCP) and their relevant services.</li> <li>Exposure to MLOps tools and concepts (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).</li> <li>Experience creating technical documentation.</li> <li>Understanding of Git for version control.</li> <li>Familiarity with containerization technologies like Docker.</li> <li>Basic knowledge of AI/ML concepts and the ML development lifecycle.</li> </ul> #LI-SS1</div></div></div> Adequate knowledge of French is required for positions in Quebec. Additional Information: Position Type: Management Job Status: Regular Term - Full Time Job Location: Canada : Ontario : Mississauga || Canada : Ontario : Toronto || Canada : Quebec : Montreal Work Arrangement: Hybrid Application Deadline: 07/03/2026 For work arrangements that are ‘Hybrid’, successful candidates must be based in Canada and report to a set Bell office for a minimum of 3 days a week. Recognizing the importance of work-life balance, Bell offers flexibility in work hours based on the business needs. Please apply directly online to be considered for this role. Applications through email will not be accepted. We know that caring for our team members is at the heart of a healthy, positive and thriving workplace. As part of our team, you’ll enjoy a comprehensive compensation package that includes a competitive salary and a wide range of benefits to support the well-being of you and your family. As soon as you join us, you'll be eligible for medical, dental, vision and mental health benefits that you can tailor to your specific needs. Plus, as a Bell team member, you'll enjoy a 35% discount on our services and access exclusive offers from our partners. At Bell, we are proud of our focus on fostering an inclusive and accessible workplace where all team members feel valued, respected, supported, and that they belong. Bell is committed to clarity in our hiring process. All roles posted are opportunities we’re actively recruiting for, unless stated otherwise. We also want to make sure that everyone has an equal opportunity to join our team. We encourage individuals who may require accommodations during the hiring process to let us know. For a confidential inquiry, email your recruiter or <a style="color:#0563c1;text-decoration:underline" href="mailto:[email protected]">[email protected]</a> to make arrangements.If you have questions or feedback regarding accessibility at Bell, we invite you to complete the <a title="" href="https://www.bce.ca/Accessibility_services/Accessibility_Feedback?brand=bce" target="_blank" rel="noopener">Accessibility feedback form</a> or visit our <a title="" href="https://www.bce.ca/Accessibility_services" target="_blank" rel="noopener">Accessibility page</a> for other ways to contact us. Artificial intelligence may be used to assess parts of your application. Please review our privacy policy (<a style="color:#0563c1;text-decoration:underline" href="https://www.phenom.com/talent-acquisition">see Phenom for details</a>) to learn more about how we collect, use, and disclose your personal information. Created: Canada, ON, Toronto Bell, one of <a href="https://reviews.canadastop100.com/top-employer-bell?lang=en" target="_blank" rel="noopener">Canada's Top 100 Employers.</a>

Intermediate AI DevOps Engineer (Toronto, ON, CA) @ Bell

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