FriendliAI
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About
FriendliAI is a platform that offers a suite of tools for building and serving custom generative AI models. It provides dedicated endpoints, containers, and serverless endpoints for deploying and running LLMs and other generative AI models. Key features include fine-tuning capabilities, robust monitoring and debugging tools, model-agnostic function calls, seamless data integration for RAG, and various integrations with other AI tools. The platform prioritizes efficiency and cost-effectiveness, offering competitive pricing and autoscaling to manage resources efficiently. FriendliAI caters to diverse user needs, from small businesses to large enterprises, supporting various model types and offering both cloud-based and on-premise solutions. The company is committed to providing high reliability and security, with guaranteed SLAs and flexible deployment options.
Platform
Task
Features
• model-agnostic function calls and structured outputs
• monitor and debug llm performance
• train and fine-tune models
• deploy custom models effortlessly
• all-in-one platform for ai agents
• accelerate generative ai inference
• efficient, fast, and reliable generative ai inference solution for production
• fine-tune and deploy llms with h100 gpus
Pricing Plans
Enterprise
$2.90 / custom• Everything in the Basic plan
• Monitor endpoints with Metrics & Logs
• Custom pricing
Job Opportunities
Software engineer - machine learning framework
FriendliAI provides a fast, cost-effective platform for deploying and managing generative AI models, including fine-tuning and monitoring capabilities.
Education Requirements:
BS (or higher) in Computer Science or a related field
Experience Requirements:
5+ years of experience in production or in high-impact research environments
Other Requirements:
Production-level experience in Python and C++
Experience developing machine learning frameworks
Experience developing GPU kernels
Experience working with generative AI models such as large language models and diffusion models
Experience developing machine learning compilers
Responsibilities:
Developing and optimizing an advanced engine for serving generative AI models, including large language models and diffusion models
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Software engineer - web full stack
FriendliAI provides a fast, cost-effective platform for deploying and managing generative AI models, including fine-tuning and monitoring capabilities.
Education Requirements:
Bachelor's degree or higher in Computer Science, or equivalent practical experience
Other Requirements:
Work experience with UI/UX design, web frontend development
Work experience with JavaScript, TypeScript
Experience in frontend development using frameworks (e.g., React, Angular, etc.)
Experience with unit tests and E2E tests
Experience in complex asynchronous processing
Experience with issues and bug tracking systems (e.g., Jira, GitHub, etc.)
Experience with complex charts and displaying methods including statistics
Development experience using visualization related frameworks
Experience in cross-browser support
Experience in B2B product development
Experience in MLOps related product development
Experience in large-scale backend engineering development
Experience in developing services utilizing various cloud services
Experience in developing frameworks and services related to Auth, Billing, Monitoring
Experience in CI / CD
Experience in startup experience or competence
Responsibilities:
Developing and deploying MLOps web frontend and backend
Working closely with AI experts and software engineers to design and implement web-based MLOps tools to support the development, deployment, and monitoring of machine learning models
Developing user-friendly web interfaces
Integrating with backend APIs and services
Ensuring the robustness and scalability of our web platform
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Software engineer - cloud backend
FriendliAI provides a fast, cost-effective platform for deploying and managing generative AI models, including fine-tuning and monitoring capabilities.
Education Requirements:
BS (or higher) in Computer Science or a related field
Experience Requirements:
5+ years of production-level experience in Python and C++
Other Requirements:
Experience developing large-scale distributed systems
Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes
Experience working on a PaaS/SaaS platform or with Service-Oriented Architectures
Experience with security and systems that handle sensitive data
Responsibilities:
Building and operating products and infrastructure for serving generative AI at scale
Building scalable and reliable services that run on GPUs across geographic regions and cloud providers
Building products that operate on Docker and Kubernetes
Building products and infrastructure at the intersection of distributed systems and machine learning
Building tools to operate services for reliability and scalability
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Ratings & Reviews
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