Job Description : Telus International AI Data Solutions or TI AI for short, has been a global leader in data services since 2005. Listed on Feb 21 on the NYSE, TI now has a market cap of $3Billion+. With Playment's acquisition on July 21, we now have a combined strength in video, images, and audio text labelling, serving the world's top ML teams. We've built a truly industry-agnostic platform to support the growing needs of our customers. Eg of our customer use cases - Automotive companies build self-driving capabilities, Agriculture companies for identify weeds & and fruit picking, Insurance companies for claim processing & and damage detection, Retail companies for shelf tracking, Drone/Satellite imagery for terrain analysis, E-commerce for cataloguing & and visual object understanding etc. Why is it important Programming in the ML world is very different from traditional software development. ML technology has 3 major components - model, compute & and data; Recent advances in GPU have made compute infinite while algorithms behind AI are evolving to a point where they would mostly become commoditised building blocks like libraries/functions in software development. For all practical purposes, ML engineers follow a virtuous cycle of labelling data, training models & and testing them. Now, throughout the last 20 years of web development, we built a lot of tooling like Git & and IDEs to help software developers write, version & and manage vast amounts of code efficiently. Now, if code to software dev is labelled data to ML, is there a need for Github of Software 2.0 Absolutely. ML end up spending 70% of their time managing/curating datasets. There's a very strong need for one platform to curate, maintain & and label datasets and all related services around it. Playment fills this need. Join us to witness & and influence the unfolding of AI, which is the largest technology wave the world will ever see. Role Description The DevOps team is responsible for the smooth operation of the production infrastructure at Telus International AI Data Solutions. We strive to excel & continuously improve on the key operational pillars (Reliability, Observability, Elasticity and Governance). We design, build and operate TI AI cloud infrastructure and supporting platforms, to provide a flawless customer experience. Must-Haves: 1. Experience in one or more CI/CD platforms such as Jenkins, CircleCI, or GitHub Actions. 2. Strong expertise in application deployment and management on Kubernetes. 3. Proficiency in setting up monitoring for application performance and infrastructure using tools like CloudWatch, Grafana, Prometheus, New Relic, or Datadog. 4. In-depth knowledge of cloud platforms, particularly AWS. 5. Strong problem-solving abilities and a track record of resolving complex technical challenges. 6. Familiarity with Infrastructure-as-Code (IaC) tools like Terraform or CloudFormation. 7. Excellent scripting and automation skills (e.g., Bash, Python, PowerShell). 8. Strong collaboration and communication skills, with the ability to work effectively in cross-functional teams. Good-to-Haves: 1. Experience with other cloud platforms such as Azure or Google Cloud Platform (GCP). 2. Knowledge of containerisation technologies like Docker and container orchestration tools like Kubernetes. 3. Familiarity with configuration management tools such as Ansible, Chef, or Puppet. 4. Understanding of security best practices in cloud environments. 5. Experience with log aggregation and analysis tools such as ELK Stack (Elasticsearch, Logstash, Kibana) or Splunk. 6. Familiarity with database technologies like MySQL, PostgreSQL, or MongoDB. 7. Knowledge of performance testing and optimisation techniques. 8. Certifications related to cloud platforms or DevOps (e.g., AWS Certified DevOps Engineer, Kubernetes certifications). 9. Strong knowledge of Linux/Unix operating systems. 10. MLops hands-on Benefits : Work with a world-class team working on a very forward-looking problem Competitive Pay Flat hierarchy Health insurance for the family
