Senior Technical Recruiter at Lambda

San Francisco, California, United States

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$155,000 – $290,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Cloud Computing, Machine LearningIndustries

Requirements

8+ years of full-cycle technical recruiting experience, preferably with high-growth startups or competitive tech companies (sourcing, screening, closing top-tier candidates)
Prior experience recruiting at a high growth start-up or at an agency servicing similar companies
Excel at evaluating candidates for both cultural alignment and deep technical competencies, particularly in cloud infrastructure, distributed systems, and infrastructure workload optimization
Demonstrate genuine passion for cloud technologies, distributed systems, and AI infrastructure with the ability to quickly understand complex technical requirements and scalability challenges
Master advanced sourcing techniques across LinkedIn Recruiter, LinkedIn Talent Insights, GitHub, cloud engineering communities, open-source projects, and specialized infrastructure platforms
Have extensive experience with modern ATS platforms and recruiting analytics tools to drive data-informed hiring decisions
Thrive in fast-paced, ambiguous startup environments where priorities shift rapidly and scrappy execution is essential
Presence in San Francisco office 4 days per week (Lambda’s designated work from home day is Tuesday)

Responsibilities

Lead end-to-end recruiting for hyper-growth AI cloud infrastructure startup, prioritizing exceptional hiring manager partnerships and candidate experiences that reflect engineering-first culture
Source, screen, and evaluate top-tier talent across cloud infrastructure, distributed systems, DevOps/SRE, and infrastructure engineering (high performance computing, networking, storage, orchestration) roles
Partner with engineering leadership and founders to develop and execute aggressive hiring strategies including competitive intelligence, talent mapping, and analysis of the cloud infrastructure market
Navigate complex technical interviews and guide decision-making processes across distributed team of interviewers and hiring managers
Leverage recruiting analytics and market insights to optimize hiring velocity, quality, and conversion rates in the competitive cloud infrastructure talent market
Build and maintain recruiting dashboards and performance metrics that support rapid platform scaling objectives
Drive continuous innovation in recruiting process, candidate experience, and employer branding to compete for the best cloud infrastructure talent globally

Skills

Technical Recruiting

Talent Sourcing

Candidate Screening

End-to-End Recruiting

Hiring Manager Partnership

Cloud Infrastructure

Distributed Systems

DevOps

SRE

High Performance Computing

Networking

AI Infrastructure

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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