Platform Engineer: Kubernetes
SupabaseFull Time
Mid-level (3 to 4 years), Senior (5 to 8 years)
Key technologies and capabilities for this role
Common questions about this position
Required skills include experience with Linux/Kubernetes systems, familiarity with infrastructure-as-code and Git-based workflows like Terraform and Flux, ability to write tooling in Go, Python, or Bash, understanding of networking fundamentals, working knowledge of storage concepts, and a strong sense of ownership.
Groq fosters a culture of humility, collaboration, growth mindset, curiosity, and innovation, where team members check egos at the door, collaborate to be the smartest together, share knowledge generously, and take creative approaches.
This information is not specified in the job description.
This information is not specified in the job description.
A strong candidate has hands-on experience provisioning bare metal servers, exposure to Talos Linux or Kubernetes platform engineering, and previous collaboration with data center, hardware, or network teams, in addition to the core required skills.
AI inference technology for scalable solutions
Groq specializes in AI inference technology, providing the Groq LPU™, which is known for its high compute speed, quality, and energy efficiency. The Groq LPU™ is designed to handle AI processing tasks quickly and effectively, making it suitable for both cloud and on-premises applications. Unlike many competitors, Groq's products are designed, fabricated, and assembled in North America, which helps maintain high standards of quality and performance. The company targets a variety of clients across different industries that require fast and efficient AI processing capabilities. Groq's goal is to deliver scalable AI inference solutions that meet the growing demands for rapid data processing in the AI and machine learning market.