Member of Technical Staff (Cloud Infrastructure)
Posted Updated
Description
- As a Software Engineer on our Cloud Infrastructure team, you’ll be at the forefront, architecting and building the foundational systems that power Fireworks AI’s revolutionary generative AI platform
- You’ll spearhead the creation of one of the world’s first virtual clouds, seamlessly serving AI workloads across the globe and every cloud provider
- Your mission: to deliver unparalleled reliability, efficiency, and scalability, fueling the world’s most innovative AI products.This is a highly technical role requiring deep expertise in distributed systems, cloud-native infrastructure, and machine learning platforms
- You’ll partner closely with engineering partners, product teams, and infrastructure stakeholders to design solutions that balance performance, cost-efficiency, and operational simplicity across compute, storage, and networking layers
- 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
- Design and implement core backend services (e.g., job schedulers, resource managers, autoscalers, model serving layers) with a focus on efficiency and low latency
- Drive infrastructure optimization initiatives, including compute cost reduction, storage lifecycle management, and network performance tuning
- Collaborate cross-functionally with ML, DevOps, and product teams to translate research and product needs into robust infrastructure solutions
- Continuously evaluate and integrate cloud-native and open-source technologies (e.g., Kubernetes, Kubeflow, MLFlow) to enhance our platform’s capabilities and reliability
- Own end-to-end systems from design to deployment and observability, with a strong emphasis on reliability, fault tolerance, and operational excellence
- Ensuring System Reliability: Ensure systems are designed and implemented with high availability, scalability, and performance. Focus on fault tolerance, disaster recovery, identifying and removing scaling bottlenecks, and performance optimization across our multi-cloud infrastructure
- Observability & Monitoring: Develop, implement, and maintain comprehensive monitoring, alerting, logging, and tracing solutions to provide deep insights into system health and performance
- 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