Member of Technical Staff, Cloud Infrastructure
$175k - $220k • Remote • San Mateo • FullTime
Posted 1y ago
About the job
As a Software Engineer on our Cloud Infrastructure team, you will architect and build the foundational systems powering Fireworks AI's generative AI platform. You will spearhead the creation of a virtual cloud for serving AI workloads globally across all cloud providers, focusing on unparalleled reliability, efficiency, and scalability. This highly technical role requires deep expertise in distributed systems, cloud-native infrastructure, and machine learning platforms, involving close collaboration with engineering partners, product teams, and infrastructure stakeholders to design solutions that balance performance, cost-efficiency, and operational simplicity.
Responsibilities
- Architect and build scalable, resilient, and high-performance backend infrastructure for distributed training, inference, and data processing.
- Lead technical design discussions, mentor engineers, and establish best practices for large-scale ML infrastructure.
- Design and implement core backend services like job schedulers, resource managers, autoscalers, and 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 with ML, DevOps, and product teams to translate needs into robust infrastructure solutions.
- Evaluate and integrate cloud-native and open-source technologies like Kubernetes, Kubeflow, and MLFlow.
- Own end-to-end systems from design to deployment and observability, emphasizing reliability and fault tolerance.
- Ensure systems are designed for high availability, scalability, and performance, focusing on fault tolerance, disaster recovery, and bottleneck removal.
- Develop and maintain comprehensive monitoring, alerting, logging, and tracing solutions.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or related technical field (or equivalent practical experience).
- 5+ years of experience designing and building backend infrastructure in cloud environments (e.g., AWS, GCP, Azure).
- Proven experience in ML infrastructure and tooling (e.g., PyTorch, TensorFlow, Vertex AI, SageMaker, Kubernetes).
- Strong software development skills in languages like Python or C++.
- Deep understanding of distributed systems fundamentals: scheduling, orchestration, storage, networking, and compute optimization.
- 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.