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Lead DevOps Engineer for AI Solutions
3 months ago
About T-Net British Columbia:
T-Net British Columbia has been a leader in enterprise information management for over two decades, providing top-tier cloud archiving, surveillance, eDiscovery, and analytics solutions. We specialize in securely capturing and preserving the communications data of highly regulated organizations, enhancing their visibility and control over information while ensuring compliance with rigorous regulations.
We pride ourselves on being more than just a technology company; T-Net is a place for innovation, creativity, and professional growth. We foster an environment where diverse ideas thrive, and employees are encouraged to collaborate and learn from one another.
Your Role:
As a Senior DevOps/MLOps Engineer on our Artificial Intelligence team, you will play a crucial role in ensuring the reliability and seamless operation of various environments. You will develop automation processes to enhance the reliability and efficiency of code and machine learning model delivery from development to production. This position offers the chance to explore new technologies and apply your expertise across diverse projects and application domains, particularly in the exciting realm of MLOps.
At T-Net, we utilize cutting-edge technologies to manage the infrastructure that supports our highly scalable and available services. Your role will involve collaborating with various teams and stakeholders to ensure product requirements are met effectively. This is a unique opportunity to influence the design and implementation of systems at an impressive scale.
Your Responsibilities:
- Automation: Create tools and frameworks to enhance our Continuous Integration (CI) and Continuous Delivery (CD) automation using industry-standard practices.
- Deployments: Utilize CI/CD automation to deploy our services on Kubernetes.
- Operations: Monitor and ensure the smooth operation of our services across different environments.
- Service Reliability: Provide support and initial troubleshooting when necessary by reviewing dashboards and logs to address system issues promptly.
About You:
- 5+ years of experience in a DevOps/MLOps role or a similar position.
- Bachelor's degree in computer science or a related field, or equivalent professional experience.
- Strong understanding of computer science fundamentals, including threading and object-oriented programming.
- Familiarity with software systems concepts such as networking, firewalls, protocols, and databases.
- Knowledge of software delivery practices, including Git branching models, configuration management, secret rotation, feature toggling, and no-downtime deployments.
- Experience mentoring junior and intermediate DevOps/MLOps professionals.
- Excellent organizational and communication skills.
- Proficiency with:
- CI/CD tools like Jenkins.
- Containerization technologies such as Docker and Kubernetes.
- Scripting languages like Python.
- Databases including CockroachDB and PostgreSQL.
- Distributed event streaming platforms like Kafka.
- Monitoring tools such as Splunk, Loki, Zabbix, or Prometheus.
- Package managers and artifact repositories like Artifactory and npm.
Preferred Qualifications:
- Experience with artificial intelligence or machine learning tools such as MLFlow, JupyterHub, DVC, or TensorFlow.
Compensation:
T-Net British Columbia adheres to pay transparency laws, and the compensation for this role includes an annual base salary, corporate bonuses, extended health benefits, and RRSP matching.
What to Expect:
At T-Net, the possibilities for your career are limitless. We provide the mentorship, coaching, and support necessary for you to achieve your professional goals. You will be part of a culture that fosters creativity and rewards hard work, collaborating with talented individuals from diverse backgrounds.
T-Net British Columbia is an equal-opportunity employer committed to diversity, equity, and inclusion. We strive to accommodate the unique needs of every individual and promote a healthy work/life balance through flexible work arrangements.
