Solutions Architect, AI/ML Cloud

Salary: $249.6K - $374.4K OTE Employment Type: Full-Time Location Type: Remote

Position Overview

Lambda is the #1 GPU Cloud for ML/AI teams training, fine-tuning, and inferencing AI models. We provide engineers with an easy, secure, and affordable platform to build, test, and deploy AI products at scale. Our product portfolio includes on-prem GPU systems, hosted GPUs across public & private clouds, and managed inference services, serving governments, researchers, startups, and enterprises worldwide. If you're passionate about building the world's best deep learning cloud, join us.

Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda website, cloud APIs and systems, as well as internal tooling for system deployment, management, and maintenance.

Responsibilities

• Advocate for Lambda’s Products:
  • Develop and maintain expertise in Lambda’s cloud products and services.
  • Demonstrate Lambda’s software and solutions to customers, partners, and staff.
  • Create field enablement materials for technical audiences, lead workshops, and support product advocacy efforts.
  • Provide technical feedback from customers to Lambda’s product and marketing teams.
• Own the Technical Side of Lambda’s Sales Process:
  • Partner with Lambda account executives to drive customer adoption and ensure successful delivery.
  • Evaluate and assess customer needs to deeply understand pain-points, bottlenecks, and expected outcomes.
  • Recommend appropriate cloud services and configurations to design cohesive solutions that support customer applications and workflows.
  • Document proposals and designs in formats including, but not limited to, presentations, white-papers, visuals, Bill of Materials, and rack elevations.
• Demonstrate Expertise on Lambda’s Cloud Infrastructure:
  • Build structured and purposeful learning into your work routine.
  • Develop and support the internal Lambda community as a subject matter expert.
  • Be an expert at deploying AI/ML workloads on Lambda cloud.
  • Stay up-to-date on the latest deep learning trends, best practices, and experiment with them using internal tools and resources.
• Develop High-Quality Processes and Documentation:
  • Reinforce Lambda’s culture.
  • Contribute positively throughout the organization.
  • Maintain a high level of agility and responsiveness.
  • Be hyper-focused on customer satisfaction.

Requirements

• 8+ years of experience designing, deploying, and scaling cloud infrastructure.
• 4+ years of experience as a solutions architect or in a consultative capacity supporting cloud infrastructure and services.
• 3+ years of experience working with cloud-based AI/ML services.
• Deep knowledge of the ML ecosystem, including common models, practical use cases, and supporting tools.
• Experience building with modern infrastructure tools such as Docker, Kubernetes, Ansible, and Terraform.
• Deep knowledge of cloud infrastructure, security, networking, and cost optimization techniques.
• Experience coding in Python, C#, or similar programming languages.
• Experience developing with NVIDIA’s GPUs.
• Have led complex technical projects with diverse stakeholders.
• Demonstrated impact at an organizational/multi-departmental level.
• Experience leading complex cloud deals, influencing C-level stakeholders, and mentoring junior SEs or architects.
• Thrive in dynamic settings and embrace radical ownership of initiatives and outcomes.

Nice to Have

• Experience with AI/ML use case to algorithm selection, training, tuning, inference, and training pipeline design and build.
• Participation in go-to-market (GTM) initiatives or product launches.
• Experience working with LLM architectures.
• Experience working with RESTful APIs and general service-oriented architecture.

About Lambda

Founded in 2012, Lambda has approximately 350 employees (as of 2024) and is growing fast. We offer generous cash &