Storage Engineering Manager at Lambda

San Jose, California, United States

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$330,000 – $495,000Compensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Machine Learning, Cloud ComputingIndustries

Requirements

Seasoned experience in the specification, evaluation, deployment, and management of HPC storage solutions across multiple datacenters
Experience building out a world-class team of storage engineers
Expertise in high-performance, petabyte-scale storage solutions, serving as the ultimate technical and operational authority
Ability to ensure systems are reliable, scalable, and manageable at exascale
Knowledge at the intersection of large-scale distributed systems and AI infrastructure

Responsibilities

Grow/hire, lead, and mentor a top-talent team of high-performing storage engineers delivering HPC, petabyte-scale storage solutions
Foster a high-velocity culture of innovation, technical excellence, and collaboration
Conduct regular one-on-one meetings, provide constructive feedback, and support career development for team members
Drive outcomes by managing project priorities, deadlines, and deliverables using Agile methodologies
Drive the technical vision and strategy for Lambda distributed storage solutions
Lead storage vendor selection criteria, vendor selection, and vendor relationship management (support, installation, scheduling, specification, procurement)
Manage team in storage lifecycle management

Skills

Distributed Storage

High-Performance Networking

Storage Protocols

GPU Hardware

Compute Virtualization

AI Clustering

Networking Hardware

Multi-Tenant Security

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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