About this role
Req Id: 431341Connection 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.At Bell, data science experts like you are shaping the future. You'll create, apply and work with algorithms that learn and analyze data, just like the human brain. By leveraging AI and machine learning technologies, you'll help us deliver better experiences and service innovations to Canadians. Plus, through our partnerships, you'll have the opportunity to learn and grow alongside other AI professionals to advance your career and make a lasting impact.SummaryWe are seeking a highly skilled and experienced Machine Learning Engineering Developer II to join our team. This role requires a strong understanding of machine learning principles, software engineering best practices, and cloud infrastructure. The ideal candidate will be responsible for the development, deployment, and maintenance of ML models and pipelines in a production environment. Key ResponsibilitiesDevelop, deploy, and maintain machine learning models in production on cloud platforms (specify preferred platforms, e.g., AWS, Azure, GCP). Design, implement, and maintain infrastructure-as-code (IaC) for ML applications, ensuring scalability, reliability, and maintainability. Develop, enhance, and maintain CI/CD pipelines for ML model development and deployment. Build, automate, and maintain machine learning dependencies and artifact pipelines, ensuring efficient and reproducible workflows. Collaborate closely with product teams to accelerate development cycles, improve product robustness, and address production issues. Proactively identify and resolve performance bottlenecks and other issues in ML pipelines and applications. Contribute to the development and improvement of ML engineering best practices and standards. Mentor and guide junior engineers. Proactive Problem-Solving:?Identifies critical needs and takes decisive action to address them effectively and efficiently. Innovation and Continuous Improvement:?Actively seeks and implements new ideas and innovative solutions, proactively exploring new areas and opportunities for growth. Customer-Centric Approach:?Demonstrates a deep understanding of customer needs, anticipating and exceeding expectations to drive customer satisfaction. Analytical and Solution-Oriented:?Masterfully applies systematic problem-solving methodologies to complex challenges, consistently delivering effective solutions. Learning Agility and Continuous Development:?Proactively investigates mistakes, fosters a culture of learning from experience, and actively seeks opportunities to expand skills and responsibilities. Mentorship and Collaboration:?Mentors and guides junior team members, fostering a collaborative environment of knowledge sharing and mutual support.Critical QualificationsBachelor's degree in Computer Science, Software Engineering, Data Science, or a related field. Relevant experience may be considered in lieu of a degree. 3+ years of experience in a machine learning engineering or related role. Cloud Associate Cloud Engineer certification (e.g., AWS Certified Cloud Practitioner, Azure Fundamentals, Google Cloud Certified Professional Cloud Architect ? specify preferred certification). Proficiency in SQL. Understanding of big data processing and parallel processing techniques like Hadoop, Kafka, Apache etc. Experience with containerization technologies (e.g., Docker, Kubernetes).