Senior Cloud Solutions Engineer

United States

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$249,600 – $374,400Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Cloud Computing, AI/ML Services, GPU Hardware & Cloud InfrastructureIndustries

Requirements

Candidates are required to possess 8 years of experience designing, deploying, and scaling cloud infrastructure, along with 4 years of experience as a solutions architect or in a consultative capacity supporting cloud infrastructure and services, and 3 years of experience working with cloud-based AI/ML services. They must have deep knowledge of the ML ecosystem, including common models, practical use cases, and supporting tools, and experience coding in Python, C#, or similar programming languages, as well as experience developing with NVIDIA’s GPUs. Furthermore, they should have led complex technical projects with diverse stakeholders and demonstrated impact at an organizational level.

Responsibilities

The Senior Cloud Solutions Engineer will advocate for Lambda’s products by developing and maintaining expertise in their cloud offerings, demonstrating them to customers and partners, and creating field enablement materials. They will own the technical side of Lambda’s sales process by partnering with account executives, evaluating customer needs, recommending appropriate cloud services, and documenting proposals and designs. Additionally, they will demonstrate expertise on Lambda’s cloud infrastructure, develop high-quality processes and documentation, and contribute positively throughout the organization while maintaining a high level of agility and responsiveness.

Skills

Cloud Solutions

AWS/Azure/GCP

AI/ML workloads

GPU computing

System deployment

Customer engagement

Technical presentations

Solution architecture

Deep learning trends

Infrastructure management

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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