Member of Technical Staff, Cluster Management
About Us:
At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
The Role:
As a Member of Technical Staff, Cluster Management at Fireworks AI, you will play a critical role in making our world-scale virtual AI cloud reliable, performant, and efficient. You will apply your expertise in large-scale distributed systems, cloud infrastructure, and operational excellence. You will partner closely with world-class software engineers and AI experts to scale cutting-edge AI platforms to meet the fast-growing demands and ever-evolving application paradigms. This role is for someone passionate about operating highly robust, observable, and automated systems and enabling customer successes.
Key Responsibilities:
- 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.
- Incident Management & Response: Lead efforts in incident detection, response, and resolution for critical production issues. Drive post-mortems to identify root causes and implement preventative measures to improve system reliability.
- Observability & Monitoring: Develop, implement, and maintain comprehensive monitoring, alerting, logging, and tracing solutions to provide deep insights into system health and performance.
- Automation & Toil Reduction: Identify and automate repetitive operational tasks to reduce toil and improve operational efficiency. Develop tools and scripts to streamline deployments, scaling, and system management.
- Capacity Planning & Performance Tuning: Work proactively on capacity planning to ensure our infrastructure can gracefully handle growth and peak loads. Optimize system performance and resource utilization.
- Reliability Best Practices: Collaborate with software engineers to embed reliability principles (e.g., SLOs, SLIs, error budgets) into the development lifecycle, promoting a culture of operational excellence.
- On-call Rotation: Participate in a periodic on-call rotation to support our production environment and respond to critical alerts.
Minimum qualifications:
- Bachelor's degree in Computer Science, related technical field, or equivalent practical experience.
- 5+ years of experience in Site Reliability Engineering, DevOps, or a similar role focused on large-scale production systems.
- Deep expertise in SRE principles and practices, including SLOs, SLIs, operational automation, incident management, and post-mortems.
- Extensive hands-on experience with public cloud platforms (AWS, GCP, Azure), including compute, networking, storage, and database services.
- Strong experience with containerization technologies (Docker) and orchestration platforms (Kubernetes).
- Proficiency in designing and implementing robust monitoring, logging, and alerting systems using tools like Prometheus, Grafana, ELK stack, and distributed tracing.
- Solid programming/scripting skills in at least one language (e.g., Python, Go) for automation and tool development.
- In-depth knowledge of Linux operating systems, networking fundamentals, and system debugging.
- Proven ability to troubleshoot complex issues across the entire stack.
- Excellent communication, collaboration, and problem-solving skills.
- Willingness to participate in on-call rotations.
Preferred qualifications:
- Experience of managing data center grade GPU clusters with GPU (and peripherals like HBM and RDMA enabled networking) monitoring, troubleshooting, and fixing.
- Experience with machine learning infrastructure, model serving, or distributed AI frameworks.
- Hands-on experience in security and data protection.
Why Fireworks AI?
- Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
- Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
- Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
- Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.