Join a Montreal headquartered company that helps organizations around the world create a personalized journey of impact and fulfillment for their people. Explorance offers innovative People Insight Solutions because we believe that each experience matters. Explorance is a rapidly growing software company recognized for its unique workplace culture. We strive to be the best we can for our people, our customers, and the community.
As a Senior DevOps Engineer, you will be at the forefront of shaping our DevOps practices, optimizing our infrastructure to support ML initiatives, and ensuring the reliability and performance of our systems. You will work closely with our ML team to deploy models effectively, enabling data-driven decision- making through Python-based APIs. If you are a seasoned DevOps professional with a passion for ML and infrastructure, we invite you to apply and be a key contributor to our success.
We are seeking an experienced and highly skilled Senior DevOps Engineer to lead our DevOps efforts, with a focus on optimizing our infrastructure and operations to support our Machine Learning (ML) initiatives. As a Senior DevOps Engineer, you will play a pivotal role in ensuring the reliability, scalability, and performance of our systems, especially in the areas of RabbitMQ, Redis caching, and Kubernetes clustering. Your expertise will be instrumental in driving our DevOps practices to the next level while working closely with our ML team to facilitate the deployment of their models through Python-based APIs.
- Infrastructure Management: Design, build, and maintain our infrastructure to support high-performance, scalable, and fault-tolerant applications, with special emphasis on ML model deployment.
- Kubernetes Expertise: Lead our Kubernetes orchestration efforts, managing and optimizing clusters to ensure efficient resource utilization and high availability, specifically tailored to support ML workloads.
- Message Queue Management: Configure, monitor, and maintain RabbitMQ message queues, ensuring seamless communication between microservices, including those powering ML workflows.
- Caching Strategies: Implement and manage Redis caching solutions to enhance application performance and reduce latency, critical for our new Blue solution.
- Automation and CI/CD: Develop and enhance CI/CD pipelines to automate application deployment, testing, and monitoring, ensuring a smooth and reliable release process for ML APIs.
- ML Model Deployment: Collaborate closely with our ML team to assist in deploying ML models through Python-based APIs, ensuring efficient and reliable model serving.
- Security and Compliance: Collaborate with security teams to establish and maintain best practices for infrastructure security, especially crucial when dealing with sensitive ML data.
- Monitoring and Troubleshooting: Implement advanced monitoring and alerting solutions to proactively identify and resolve performance bottlenecks, system outages, and application issues related to ML services and other services.
- Collaboration and Mentoring: Work closely with cross-functional teams, providing technical leadership, mentorship, and support to junior DevOps team members and collaborating seamlessly with the ML team, CloudOps, SecOps.
- Experience: A minimum of 3 years of hands-on experience in a DevOps or infrastructure-related role, with a strong focus on Kubernetes, RabbitMQ, Redis, Python, and ML model deployment.
- Kubernetes Mastery: Demonstrated expertise in Kubernetes administration, including cluster setup, management, and optimization for ML workloads.
- Message Queue Proficiency: Proven experience with RabbitMQ or other message queuing systems, including message broker patterns, and troubleshooting in an ML context.
- Caching Expertise: Familiarity with Redis caching strategies, especially for caching ML predictions and data.
- DevOps Tools: Familiarity with version control systems (e.g., Git), CI/CD tools (e.g., Jenkins, GitLab CI/CD), and configuration management tools (e.g., Ansible, Puppet)
- Scripting and Automation: Proficiency in Python programming, scripting languages, and experience with infrastructure as code tools.
- CI/CD Tools: Strong knowledge of CI/CD tools and practices, particularly for deploying Python-based ML APIs.
- Cloud Experience: Familiarity with cloud platforms like Azure is a plus.
- Linux Administration: Solid understanding of Linux-based operating systems and shell scripting.
- Experience with other containerization technologies (e.g., Docker) and container orchestration platforms (e.g., Kubernetes).
- Familiarity with microservices, architecture and deployment.
- Previous experience in mentoring or leading a DevOps team.
- Only apply if you are a Montreal (or surroundings) resident that is interested in being part of a vibrant and highly engaged at-the-office culture.
At Explorance, we take inclusion to heart and live it each day. We put the ‘human’ first in everything we do and take pride in our authenticity and culture of inclusion. We therefore encourage persons of any race, religion, ethnicity, gender identity, sexual orientation, age, immigration status, disability or other applicable legally protected characteristics to apply. We make employment-related decisions without regard to any of these characteristics. And to ensure a safe workspace for all our employees, all employment is contingent upon receipt of a satisfactory background and reference check.
Founded in 2003, Explorance supports more than 20 million people in their individual journeys of purpose, growth, and impact. As the leading provider of Feedback Analytics Solutions, Explorance empowers organizations with actionable decision-making by measuring students’ and employees’ needs, expectations, skills, knowledge, and competencies. Explorance facilitates continuous improvement and accelerates the insight-to-action cycle leading to personal growth and organizational agility. Headquartered in Montreal with business units in Chicago, Chennai, Melbourne, Amman, and London. Explorance works with 25% of the Fortune 100 and 30% of the top Higher Education institutions, including 8 of the world’s top 10 business schools. The company has clients in more than 50 countries.