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Fireworks AI

AI inference platform for model deployment

Member of Technical Staff - LLM Infrastructure

Applied Machine LearningConfirmed live in the last 24 hours
Full-time$175k - $220k /yrHybrid

About the Job

Requirements

  • A bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • At least 3 years of software engineering experience focused on infrastructure or machine learning systems.
  • Strong programming skills in Python, Go, or a similar language.
  • Experience with machine learning infrastructure and tooling, such as PyTorch, MLflow, Vertex AI, SageMaker, or Kubernetes.
  • Basic understanding of large language model concepts, including context length, disaggregated prefill, and key-value cache memory estimation.

Responsibilities

  • Contribute to the design and development of scalable backend infrastructure supporting distributed training, inference, and data pipelines.
  • Build and maintain core backend services, including large language model continuous integration and continuous delivery pipelines, control plane, and model-serving systems.
  • Support performance optimization, cost efficiency, and reliability improvements across compute, storage, and networking layers.
  • Build frameworks and safeguards to ensure model quality.
  • Collaborate with performance, training, and product teams to translate research and product needs into infrastructure solutions.
  • Participate in code reviews, technical discussions, and continuous integration and deployment processes.

Desired Qualifications

  • At least 5 years of software engineering experience focused on infrastructure or machine learning systems.
  • Experience with open-source inference engines such as vLLM, SGLang, or TRT-LLM.
  • Contributions to open-source infrastructure or machine learning projects.
  • Experience building large-scale machine learning and MLOps infrastructure.

About the Company

Fireworks AI

AI inference platform for model deployment

Fireworks AI provides an AI inference platform that helps organizations run, customize, and deploy machine learning models. It supports deployment, fine-tuning, and inference workflows, with access to open-source models and on-demand deployment options through a subscription model. The platform enables users to configure and optimize models for production environments, manage variants, and scale AI workloads while controlling costs. Unlike some competitors, the emphasis is on end-to-end production-grade inference and fine-tuning across a range of clients, from tech firms to research institutions and enterprises, with tools tailored for rapid deployment and cost efficiency. The long-term goal is to expand the use of AI in production by building compound AI systems, growing the team, and delivering broader platform capabilities that accelerate AI adoption in real-world settings.

Company size
201-500
Company stage
Series D
Total funding
$1.8B
Headquarters
Redwood City, CA
Founded
2022

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