Lambda

Machine Learning Research Intern - 2025 Summer

San Francisco, California, United States

Not SpecifiedCompensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
AI & Machine Learning, Consumer SoftwareIndustries

Requirements

Candidates must be Ph.D. students in Computer Science or a related field with a focus on machine learning. Experience publishing in top-tier machine learning conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, or Siggraph is required. Proficiency in PyTorch or similar frameworks and strong communication skills are essential. Contributions to open-source projects and experience with generative AI, dataset pipeline design, and training foundation models are preferred.

Responsibilities

The Machine Learning Research Intern will develop datasets to support efficient model training, build and improve generative AI models, and set new standards for evaluating generative AI performance. Interns will leverage Lambda's compute resources to produce impactful research through publications and open-source contributions.

Skills

PyTorch
Machine Learning
Dataset Development
Model Building
Generative AI
Evaluation Methods
Communication Skills

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.

Key Metrics

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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