Staff Cloud DevOps/Site Reliability Engineer (SRE) - Canada at Inworld
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Why Join Inworld
Inworld is the best-funded startup in AI and gaming with a $500 million valuation and backing from top tier investors like Intel, Microsoft, Lightspeed, Bitkraft, Founders Fund, Kleiner Perkins, and more. Inworld was recognized by CB Insights list of the 100 most promising AI companies in the world. We’ve also been nominated alongside Anthropic, DeepMind, OpenAI and Nvidia for the Generative AI Innovator of the Year at the VentureBeat Awards 2023, and are a Gartner Cool Vendor in 2023.
Inworld is the leading character engine for creating AI NPCs in games and immersive entertainment. Inworld powers NPCs in experiences built by Niantic, NetEase Games, LG, Alpine Electronics, the Disney Accelerator, and more. We go beyond large language models (LLMs) to add multimodal orchestration of personality and contextual awareness that renders NPCs within the lore and logic of their worlds.Â
We are looking for a Staff Cloud DevOps/Site Reliability Engineer to keep the Inworld systems up and running with the highest level of availability, security, and performance.
Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related field
- 6+ years of experience as a site reliability engineer, DevOps, and/or MLOps engineer
- Experience administering and troubleshooting Linux systems
- Understanding of CI/CD pipelines and Infrastructure as a Code (Terraform or similar)
- Experience working with cloud environments like AWS, Azure, or Google Cloud
- Experience with Python or GolangÂ
- Experience with developer tools, productivity, or operations automation
- Experience with orchestrating big containerized deployments (Kubernetes - GKE/EKS or similar)
- Experience with setting up logging and monitoring pipelines (Prometheus, Grafana, Datadog, etc.)
- Knowledge of different deployment strategies
- Experience with high-performance and high-available distributed NoSQL and SQL databases, analytics engines, message brokers, and queueing systems
- Experience in designing , building and maintaining Machine Learning Inference or/and training infrastructure is considered a plus
Responsibilities
- Work alongside the engineering team to ensure the delivery, scalability, and reliability of the Inworld services
- Measure and monitor availability, latency, and overall service health
- Create and support CI/CD pipelines
- Organize multistage deployment environments
- Drive incident management and post-mortem analysis
In-office location: Vancouver, Canada.
Remote location: Canada.