Member of Technical Staff (Cloud Infrastructure)

Join Fireworks AI as a Member of Technical Staff (Cloud Infrastructure). In this highly technical role, you will architect and build the foundational systems that power our revolutionary generative AI platform. You will lead the creation of a virtual cloud that serves AI workloads globally and across all cloud providers. Your mission will be to deliver unparalleled reliability, efficiency, and scalability, fueling the world's most innovative AI products. You will collaborate closely with engineering partners, product teams, and infrastructure stakeholders to design solutions that balance performance, cost-efficiency, and operational simplicity.

• Architect and build scalable, resilient, and high-performance backend infrastructure to support distributed training, inference, and data processing pipelines.
• Lead technical design discussions, mentor other engineers, and establish best practices for building and operating large-scale ML infrastructure.
• Drive infrastructure optimization initiatives, including compute cost reduction, storage lifecycle management, and network performance tuning.

• Proven experience in ML infrastructure and tooling (e.g., PyTorch, TensorFlow, Vertex AI, SageMaker, Kubernetes, etc.)
• Strong software development skills in languages like Python, or C++
• Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
• 5+ years of experience designing and building backend infrastructure in cloud environments (e.g., AWS, GCP, Azure)
• Deep understanding of distributed systems fundamentals: scheduling, orchestration, storage, networking, and compute optimization
• Master’s or PhD in Computer Science or related field
• Experience leading infrastructure projects supporting large-scale ML/AI workloads or high-throughput systems
• Familiarity with infrastructure-as-code and CI/CD tooling (e.g., Terraform, ArgoCD, GitOps)
• Track record of driving system performance, reliability, and cost-efficiency improvements
• Contributions to open-source cloud or ML infrastructure projects a plus