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Full-Time

Recruiting Coordinator

Posted on 6/12/2024

Lambda

Lambda

51-200 employees

Cloud-based GPU services for AI training

AI & Machine Learning

Compensation Overview

$68k - $90kAnnually

+ Cash & Equity Compensation

Junior

San Francisco, CA, USA

Requires onsite presence in San Francisco, California for four days per week. Work from home day is Tuesday.

Category
Generalist Recruiting
People & HR
Required Skills
Applicant Tracking Software (ATS)
Communications
Requirements
  • 2-3 years of recruiting coordination, executive assistant, or related coordination experience
  • Comfortable working in dynamic work environments
  • Strong organizational skills and attention to detail
  • Demonstrated ATS experience
  • Proficient with GSuite (Gmail, Google Calendar, Docs, Sheets)
  • Effective communication skills verbally and in written form
  • Ability to manage multiple tasks, priorities, and deadlines in a fast-paced recruitment environment
  • Keen attention to detail for accuracy in recruitment coordination activities
  • Problem-solving skills to identify and address issues in recruitment processes
  • Flexibility to navigate changing priorities and challenges
  • Commitment to providing an exceptional candidate experience
Responsibilities
  • Schedule all phone/virtual interviews, prep calls, and candidate debriefs
  • Coordinate candidate interactions with internal teams and interviewers
  • Provide follow-up correspondence to candidates
  • Assist in coordinating other recruiting activities
  • Identify and implement solutions to streamline workflows
  • Monitor vendor performance and address issues
  • Oversee candidate experience throughout the recruitment process

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, 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.

Company Stage

Series C

Total Funding

$932.2M

Headquarters

San Jose, California

Founded

2012

Growth & Insights
Headcount

6 month growth

30%

1 year growth

72%

2 year growth

292%
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Simplify's Take

What believers are saying

  • Lambda Labs' competitive pricing and availability have attracted high-profile clients like Voltron Data, indicating strong market demand.
  • The recent $500M GPU-backed financing facility will enable Lambda to expand its cloud infrastructure significantly, enhancing service capabilities.
  • The appointment of Peter Seibold as CFO, with his extensive experience, is likely to strengthen Lambda's financial strategy and operational efficiency.

What critics are saying

  • The rising prices of AI cloud compute instances could deter cost-sensitive clients, impacting Lambda's customer acquisition.
  • The competitive landscape, with giants like AWS launching high-core instances, poses a threat to Lambda's market share.

What makes Lambda unique

  • Lambda Labs leverages NVIDIA's GH200 Grace Hopper™ Superchip, offering unmatched efficiency and price for AI training and inference, setting it apart from competitors.
  • Their Lambda Stack software simplifies AI-related software installation and upgrades, used by over 50,000 machine learning teams, providing a significant edge in user experience.
  • The Lambda Echelon service allows clients to take ownership of their infrastructure, a unique offering compared to traditional cloud service models.

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