We are seeking a highly experienced and strategic technical leader to oversees datacenter network infrastructure across Singapore and five regional markets, managing a team of 10+ network professionals.
Responsibilities
Lead and manage Enterprise network team, fostering a high-performance culture
Collaborate with multiple internal teams (Infrastructure, Security, Applications and compliance) to drive holistic solutions
Build and scale training libraries and infrastructure for autonomous driving models, enabling training on thousands of GPUs and massive datasets.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 224,000 USD – 356,500 USD for Level 5; and 272,000 USD – 431,250 USD for Level 6.
Responsibilities
Crafting, scaling, and hardening deep learning infrastructure libraries and frameworks for training on multi-thousand GPU clusters.
Improving efficiency throughout the training stack: data loaders, distributed training, scheduling, and performance monitoring.
Building robust training pipelines and libraries to handle massive video datasets and enable rapid experimentation.
Collaborating with researchers, model engineers, and internal platform teams to enhance efficiency, minimize stalls, and improve training availability.
Owning core infrastructure components such as orchestration libraries, distributed training frameworks, and fault-resilient training systems.
Build and scale deep learning infrastructure libraries and frameworks for autonomous driving models.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 224,000 USD – 356,500 USD for Level 5; and 272,000 USD – 431,250 USD for Level 6.
Responsibilities
Crafting, scaling, and hardening deep learning infrastructure libraries and frameworks for training on multi-thousand GPU clusters.
Improving efficiency throughout the training stack: data loaders, distributed training, scheduling, and performance monitoring.
Building robust training pipelines and libraries to handle massive video datasets and enable rapid experimentation.
Collaborating with researchers, model engineers, and internal platform teams to enhance efficiency, minimize stalls, and improve training availability.
Owning core infrastructure components such as orchestration libraries, distributed training frameworks, and fault-resilient training systems.
Deploy, validate, and support the datacenter network infrastructure behind Groq's global AI infrastructure using hands-on datacenter networking fundamentals.
Compensation
The total cash salary range for this position, which is inclusive of the potential bonus value, is $245,800 - 365,200, with individual placement determined by your geographic location, experience, skills, and alignment with internal compensation standards.
Responsibilities
Deploy and validate network infrastructure across new and existing Groq datacenters
Configure and validate switches, network interfaces, optics, cabling, and supporting infrastructure
Develop and maintain detailed cutsheets, port-maps, cabling plans, and implementation procedures
Validate physical connectivity and optical performance
Troubleshoot network and hardware failures across switches, optics, cabling, and servers
Lead technical program management for new cloud services and hardware platforms, driving delivery, quality, and scalability.
Locations (3)
Redmond, Washington, United States
San Francisco, California, United States
New York City, New York, United States
Compensation
The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Responsibilities
Manage introduction of new cloud services, hardware platforms and tools/processes
Work with partner engineering teams to meet scale and cycle time specifications
Analyze data to prototype and implement technical and process improvements
Network Engineer Deployment & SupportGroq · Dallas-FortWorth, US