[Remote] Manager, Support Enablement at Lambda

United States

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Not SpecifiedCompensation

N/AExperience Level

N/AJob Type

Not SpecifiedVisa

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Requirements

Experience in technical support, enablement, or a related field with a track record of developing talent
Skilled at creating structured learning programs, technical documentation, and onboarding guides
Know how to mentor and coach junior engineers, balancing technical rigor with approachability
Understand the dynamics of scaling support organizations and can define frameworks for growth, progression, and excellence
Communicate clearly and effectively, both in writing and verbally, across technical and non-technical audiences
Organized, proactive, and capable of managing multiple enablement initiatives simultaneously

Responsibilities

Design and lead support training and development programs
Create and deliver training, career frameworks, and onboarding programs for support engineers
Guide junior support engineers through their technical development and mentorship
Define clear leveling frameworks and promotion paths to facilitate career growth within Lambda
Create training material, including break/fix scenarios, troubleshooting guides, and playbooks
Design and maintain hiring and onboarding resources that set new hires up for success
Ensure the support team delivers consistently at a high standard while growing their technical confidence
At times, work periods evening or overnight hours as needed to provide training or onboarding support for employees
Work cross-functionally with product, engineering, and operations to align support enablement with broader company goals
Develop scalable systems that make teams stronger over time

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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