Storage Protocols Engineering Manager at Lambda

San Francisco, 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

Experienced Software Engineering Manager with a history in the development of storage protocols and distributed storage systems
Expertise at the intersection of high-performance distributed storage solutions and protocols, dynamic networking, and compute virtualization

Responsibilities

Grow/hire, lead, and mentor a top-talent team of high-performing software engineers focused on delivering distributed storage protocols
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 distributed storage protocols (e.g., S3, NFS, iSCSI) and their underlying distributed systems
Oversee the development of highly optimized storage solutions designed to meet the performance demands of AI/ML workloads (e.g., high throughput, low latency, optimization for AI workload access patterns)
Lead the team in tackling complex distributed systems challenges, including concurrency, consistency, fault tolerance, and data durability across multiple data centers
Guide engineering team in problem identification, requirements gathering, solution ideation, and stakeholder alignment on engineering requirements

Skills

Key technologies and capabilities for this role

Storage ProtocolsDistributed StorageHigh-Performance NetworkingDynamic NetworkingGPU ClusteringCompute VirtualizationAI Infrastructure

Questions & Answers

Common questions about this position

What is the salary range for the Storage Protocols Engineering Manager position?

The salary range is $330K - $495K.

Is this role remote or hybrid, and what are the office requirements?

This is a hybrid position requiring presence in the San Francisco office 4 days per week, with Tuesday designated as the work-from-home day.

What skills and experience are required for this engineering manager role?

The role requires experience in the development of storage protocols and distributed storage systems, with a focus on building high-performance implementations of object, block, and file protocols for AI workloads.

What is the work environment like at Lambda?

Lambda builds the world's best deep learning cloud for ML/AI teams, with Engineering responsible for scaling cloud offerings including high-performance networking and storage for AI clusters in a collaborative environment.

What makes a strong candidate for this Storage Protocols Engineering Manager role?

A strong candidate has experience developing storage protocols and distributed storage systems, plus the ability to grow, hire, lead, and mentor a team of high-performing software engineers focused on distributed storage for AI.

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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