[Remote] Advanced Cooling Facilities Manager at Lambda

United States

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Not SpecifiedCompensation

N/AExperience Level

N/AJob Type

Not SpecifiedVisa

N/AIndustries

Requirements

Deep domain expertise in liquid cooling technologies
Critical facilities management experience
Experience with Direct Liquid Cooling (DLC) systems
Experience with Coolant Distribution Units (CDUs) (L2L and L2A)
Experience with multi-stage cooling loops
Experience with data center design and mechanical engineering
Experience with vendor engagement and technical specifications
Experience with predictive and preventive maintenance methodologies
Experience with data center capacity planning
Experience with data center infrastructure planning and scaling

Responsibilities

Lead the global strategy, implementation, and operational excellence of liquid cooling infrastructure
Define methodologies and standards for the deployment, optimization, and scaling of cooling systems
Drive the design and operation of complex cooling ecosystems
Work cross-functionally with internal and external experts to establish best practices
Evaluate emerging cooling technologies
Ensure cooling infrastructure scales reliably and efficiently to support extreme rack densities
Define and oversee operational standards and lifecycle management for all CDU systems
Utilize advanced analytics to identify trends and implement predictive maintenance practices
Lead the design and management of multi-stage cooling loops
Coordinate and validate integration of CDUs with facility water systems, heat exchangers, and mechanical infrastructure
Architect the monitoring framework for coolant system telemetry
Design and institutionalize maintenance methodologies
Evaluate and forecast thermal capacity requirements
Partner with data center design and mechanical engineering teams to co-develop cooling topologies
Act as the primary technical authority for liquid cooling vendor engagement
Evaluate and pilot next-generation cooling technologies and automation platforms

Skills

Lambda

Cloud-based GPU services for AI training

About Lambda

Lambda Labs provides cloud-based services for artificial intelligence (AI) training and inference, focusing on large language models and generative AI. Their main product, the AI Developer Cloud, utilizes NVIDIA's GH200 Grace Hopper™ Superchip to deliver efficient and cost-effective GPU resources. Customers can access on-demand and reserved cloud GPUs, which are essential for processing large datasets quickly, with pricing starting at $1.99 per hour for NVIDIA H100 instances. Lambda Labs serves AI developers and companies needing extensive GPU deployments, offering competitive pricing and infrastructure ownership options through their Lambda Echelon service. Additionally, they provide Lambda Stack, a software solution that simplifies the installation and management of AI-related tools for over 50,000 machine learning teams. The goal of Lambda Labs is to support AI development by providing accessible and efficient cloud GPU services.

San Jose, CaliforniaHeadquarters

2012Year Founded

$372.6MTotal Funding

DEBTCompany Stage

AI & Machine LearningIndustries

201-500Employees

Risks

Nebius' holistic cloud platform challenges Lambda's market share in AI infrastructure.

AWS's 896-core instance may draw customers seeking high-performance cloud solutions.

Existential crisis in Hermes 3 model raises concerns about Lambda's AI model reliability.

Differentiation

Lambda offers cost-effective Inference API for AI model deployment without infrastructure maintenance.

Nvidia HGX H100 and Quantum-2 InfiniBand Clusters enhance Lambda's AI model training capabilities.

Lambda's Hermes 3 collaboration showcases advanced AI model development expertise.

Upsides

Inference API launch attracts enterprises seeking low-cost AI deployment solutions.

Nvidia HGX H100 clusters provide competitive edge in high-performance AI computing.

Strong AI cloud service growth indicates rising demand for Lambda's GPU offerings.

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