Sr. Staff Software Engineer, Inference Platform
Sunnyvale, CA • FullTime
Posted 4mo ago
Job Location
Sunnyvale, CA
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
AI Infrastructure Engineer
About the job
Cerebras Systems is seeking a Staff Engineer to join their Inference Platform team. This role will focus on the orchestration layer responsible for running inference on datacenter clusters, bridging cloud components with machine learning services. The team tackles novel challenges in areas like Kubernetes operators, service security, and CI/CD, aiming to build the next-generation architecture for a globally distributed inference platform.
Responsibilities
- Design, develop, test, and maintain production software across testing, development, observability, security, networking, debugging, and productionization.
- Enhance the effectiveness of senior engineers through design feedback, pairing, and establishing clear technical standards.
- Shape the technical direction of the Inference Platform, including Kubernetes custom resource definitions, failure domains, service boundaries, and system evolution, owning the roadmap for key technical areas.
- Architect active-active systems with rapid failover, graceful degradation, and clear SLOs, driving system-level improvements in latency, throughput, capacity efficiency, and resilience.
- Write and review production code for critical platform components, making high-consequence architectural decisions and setting technical standards through reviews.
- Lead resolution of complex production issues and cross-system bottlenecks, driving observability, incident response, capacity planning, and post-incident improvements.
- Partner with ML, Product, Infrastructure, and Cloud teams to translate requirements into scalable system designs and align on technical decisions.
Requirements
- 8+ years of software engineering experience, with significant individual contributor experience in building and operating large-scale distributed systems or cloud infrastructure.
- Deep expertise in distributed systems architecture, preferably with Kubernetes.
- Proven track record of making sound architectural decisions for highly available, latency-sensitive systems at scale.
- Experience with security concepts such as certificates, TLS, and mTLS.
- Experience optimizing latency, throughput, and efficiency in high-QPS systems; TTFT and tail-latency reduction are a strong plus.
- Strong proficiency in backend or systems languages like Go or C++, capable of contributing production code.
- Experience designing and implementing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLO-driven operations.
- Ability to influence senior engineers and cross-functional partners through technical credibility, communication, and judgment.
Benefits
- Build a breakthrough AI platform beyond the constraints of the GPU.
- Publish and open source cutting-edge AI research.
- Work on one of the fastest AI supercomputers in the world.
- Enjoy job stability with startup vitality.
- A simple, non-corporate work culture that respects individual beliefs.