The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive engineers to play a pivotal role in the development/maintenance of industry-leading multi-modal and multi-lingual large language models (LLM). AGI team's mission is to leverage our hyper-scalable, general-purpose large model training and inference systems to develop and deploy cutting-edge sensory AI foundational models that revolutionize machine perception, interpretation and interaction, with humans and with the physical world.

We believe in “Work Hard. Have Fun. Make History” value by having a strong focus on sharing learning experiences from the front line with the development teams. So, the options for people in the team are vast. If you like mastering a domain and going deep, we need you. If you can juggle three tasks and coordinate with multiple people in the heat of an incident, we need you. If you love the benefits of process and methodical improvement, you will love it here. If you want to keep your head down, headphones on, and bash out code to support the team, we have a spot for you too.

You will be required to deeply understand technology landscapes, and evaluate the use of new technologies. You will be influential within your team and work with peers and senior leaders to define and revise the standards for operational excellence across systems. You will consistently tackle abstract issues that span multiple functional areas and drive your team to push for improvements that can scale across other teams, services, and platforms.


Key job responsibilities
Provide support for cluster and node management, ensuring smooth operation of LLM infrastructure.
Continuously improve and automate our cluster/capacity/maintenance upgrades.
Develop automation tools for improving operational excellence.
Work on operations and maintenance driven coding projects, primarily in Ruby, Rails, Java, Python, or shell scripts, AWS, web technologies projects.
Should have hands-on experience in Kubernetes and expertise in different AWS services.
Drive Company Wide Campaigns with Support and Engineering teams and drive it to closure.
Participate in design and code reviews and identify bottlenecks.
Troubleshoot and research root causes throughly and resolve defects.