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Senior Software Engineer, AIOps Platform
Not specifiedFull-timeBackend DevelopmentSemiconductorsAI Infrastructure
Build distributed software for an AI operations platform that monitors GPU clusters, analyzes telemetry, and serves predictive models in SaaS and on-premises environments.
Responsibilities
- Architect and build systems that monitor GPU fleet health, correlate telemetry, generate alerts, and coordinate diagnostic and corrective workflows.
- Design distributed systems for high-volume telemetry ingestion, processing, and real-time analysis.
- Evaluate data storage strategies and representations to support high-quality data for predictive models.
- Instrument services with metrics, logs, and traces to support debugging and performance improvements.
- Build and maintain infrastructure for packaging, versioning, deploying, and monitoring predictive models across SaaS and on-premises environments.
- Develop shared libraries and abstractions for the AIOps engineering team.
Requirements
- Bachelor’s or master’s degree in computer science, computer engineering, or a related technical field.
- At least 8 years of software engineering experience building production distributed systems.
- Expert-level proficiency in Go, C++, or Rust, with experience in high-performance concurrent architectures.
- Strong understanding of Kubernetes and container-based production deployments.
- Experience deploying, monitoring, and maintaining machine learning models or data-intensive services in production.
Nice to have
- Experience building scalable model-serving platforms or MLOps tools such as model registries, rollout frameworks, or feature stores.
- Experience taking prototypes to stable production platforms for enterprise customers.
- Ability to develop tools and frameworks that help engineering teams work more efficiently.
Benefits
- Competitive salary
- Generous benefits package