Dev. Machine Learning Engineering II
Bell Canada13 days ago
Toronto, CanadaMid Level
Responsibilities
- Develop, deploy, and maintain production machine learning models on cloud platforms.
- Design and maintain infrastructure-as-code for scalable and reliable ML applications.
- Develop and maintain CI/CD pipelines for ML model development and deployment.
- Build and automate machine learning dependency and artifact pipelines.
- Collaborate with product teams to improve development cycles, product robustness, and production issue resolution.
- Identify and resolve performance bottlenecks in ML pipelines and applications.
- Improve ML engineering standards and best practices.
- Mentor and guide junior engineers.
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field, or relevant equivalent experience.
- At least 3 years of experience in machine learning engineering or a related role.
- Cloud Associate Cloud Engineer certification, such as AWS Certified Cloud Practitioner, Azure Fundamentals, or Google Cloud Certified Professional Cloud Architect.
- Proficiency in SQL and Python or a similar programming language.
- Understanding of big data and parallel processing technologies such as Hadoop and Kafka.
- Experience with Docker, Kubernetes, cloud computing, CI/CD, DevOps practices, software development lifecycle, and machine learning lifecycle methodologies.
- Experience with version control systems such as Git.
- Strong problem-solving, analytical, communication, independent-work, and teamwork abilities.
- Preferred experience with AWS, Azure, or GCP; Airflow or Argo; and Prometheus or Grafana.
- Contributions to open-source projects are preferred.
- Adequate knowledge of French is required for positions in Quebec.
Benefits
- Medical, dental, vision, and mental health benefits are available upon joining.
- 35% discount on Bell services and access to exclusive partner offers.
- Hybrid work arrangement in Toronto, Canada, requiring at least three days per week in a Bell office.
- Regular full-time position with flexible work hours based on business needs.
Tech Stack
Apache AirflowApache HadoopApache KafkaArgo CDAWSAzureDockerGitGoogle Cloud PlatformGrafanaKubernetesPrometheusPythonSQL