AI Platform Engineer

You will own a dedicated multi-GPU inference platform across its operating system, storage, networking, observability, model-serving stack, and user access. You will deploy and benchmark open-weight models, manage routing and quotas, document the platform, support integrations, and teach engineers how to use it effectively.

Responsibilities

• Collaborate with IT to manage the GPU server lifecycle across operating systems, storage, and networking
• Implement observability and alerting for GPU utilization, thermals, memory, latency, and throughput
• Build and operate the model inference stack
• Deploy, upgrade, and tune open-weight models
• Evaluate and benchmark new models for quality, throughput, and latency
• Recommend which models to run
• Manage quotas, routing, and cost and usage reporting across teams
• Optimize cloud model usage when needed
• Support developers integrating internal models into IDE assistants, agents, CI pipelines, and applications
• Maintain API keys, endpoints, and documentation
• Write self-service onboarding guides
• Run workshops and office hours
• Design queueing and workload-prioritization approaches

Requirements

• Have coding and Infrastructure as Code skills
• Know Ansible, Terraform, Docker, or Kubernetes
• Have Linux systems administration experience covering networking, storage, containers, systemd, and troubleshooting
• Understand the open-weight model ecosystem
• Communicate in English
• Demonstrate a service-oriented approach to supporting engineers and documenting systems

Benefits

• Option to be paid in bitcoin
• Flexible working hours
• Professional development budget for training, courses, and workshops
• Regular company events and social gatherings
• Office gym
• Massages
• Football table
• Billiards
• PlayStation
• 3D printer
• Free on-site parking
• MultiSport card
• Company mobile phone tariff
• Yoga classes
• Fitness classes