Engineering Program Manager - Fleet Engineering at Lambda

San Francisco, California, United States

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$226,000 – $377,000Compensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Cloud Computing, High-Performance ComputingIndustries

Requirements

10+ years of infrastructure experience with 5+ years performing program management for major projects including capital projects or hyperscaler infrastructure deployment
Demonstrated experience leading a team of engineers on complex, cross-functional projects in a fast-paced environment
Comfortable managing cross functional teams and driving decisions and communications
Experience successfully designing and implementing simple, scalable processes that solve complex problems
Thrive in ambiguous, fast-paced environments, bringing clarity and order to the team
Bachelor's degree in Computer Science, Engineering, or a related technical field
Proven track record of successfully leading and delivering complex technical projects
Exceptional leadership, communication, and interpersonal skills
Ability to thrive in a fast-paced, high-pressure environment and manage multiple projects simultaneously
Technical expertise in infrastructure technologies, including NVIDIA GPUs, hardware troubleshooting, lab methodologies, and automation tools. (Nice to Have: Experience managing hybrid hardware deployment and software engineering projects.)

Responsibilities

Partner with Fleet Engineering Managers to ensure the teams are aligned on expectations, track progress towards deliverables, providing repeatable & scalable programs
Identify opportunities for improvement: ensuring we are capturing the appropriate signals throughout the program and facilitating continuous improvement
Work with Fleet Engineering Deployments on executing against tight deadlines while improving process, tooling, automation
Collaborate closely with a broad set of stakeholders, including Platform & Infrastructure engineering, Program Management, Product Management, DC Operations, and finance
Lead cross-functional engineering teams to deliver complex infrastructure projects from concept to deployment. Define scope, goals, and deliverables; plan resources, timelines, risks and ensure execution aligns with organizational objectives
Drive risk management and stakeholder communication by proactively identifying issues, driving realtime and inflight tight timeline projects, and providing transparent updates on progress and milestones
Continuously refine project management processes to improve efficiency, collaboration, and cross-functional alignment with product, operations, and security teams. Maintain a customer-focused approach in defining and meeting technical requirements

Skills

Key technologies and capabilities for this role

Program ManagementCross-Functional CoordinationRisk ManagementMetricsAutomationProcess ImprovementNVIDIA GPUFleet EngineeringInfrastructure EngineeringDeploymentsTooling

Questions & Answers

Common questions about this position

What is the salary range for the Engineering Program Manager role?

The salary range is $226K - $377K.

Is this position remote or hybrid?

The position is hybrid.

What experience is required for this role?

Candidates need 10+ years of experience, along with technical expertise in infrastructure technologies including NVIDIA GPUs, hardware troubleshooting, lab methodologies, and automation tools.

What does the Fleet Engineering team do?

The Fleet Engineering team is responsible for the logical deployment of cutting edge NVIDIA GPU clusters, the reliability of the production fleet, and the tools and processes to support these outcomes.

What should I include in my application if I don't perfectly match the requirements?

The company values diverse backgrounds and encourages candidates who do not exactly meet the description but believe they may be a good fit to apply and explain their readiness for the role.

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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