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Java Developer

Clera

midpermanentbackenddevops Los Angeles Yesterday via RemoteOK

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Tags

JavaJVMKubernetesDockerDistributed SystemsCloud-NativeGitOpsGPU SchedulingML InfrastructureHigh-Performance Computing

About the role

Role Overview

Join Clera’s small, high-impact engineering team as a Java Developer. You’ll build backend services and infrastructure tooling that power Clera’s distributed systems platform for GPU-intensive AI workloads.

What You’ll Do

  • Translate customer requirements into robust, scalable Java solutions.
  • Design, develop, and maintain backend services and infrastructure tooling.
  • Collaborate with product and infrastructure engineers to deliver features end-to-end.
  • Improve reliability and performance for systems supporting:
    • AI inference pipelines
    • Distributed training
    • Storage orchestration
    • GPU scheduling workloads
  • Participate in code reviews, architectural discussions, and continuous improvements to engineering practices.

Requirements

  • Solid hands-on experience with Java and the JVM ecosystem.
  • Familiarity with distributed systems and cloud-native environments.
  • Experience with Kubernetes and containerization (Docker) or related infrastructure tooling.
  • Strong problem-solving skills in a fast-paced, early-stage environment.
  • Clear communication skills for direct collaboration within a small team.

Nice to Have

  • Experience with GitOps workflows/tools (e.g., Flux, Argo CD).
  • Exposure to GPU scheduling, ML infrastructure, or high-performance computing (HPC) environments.
  • Familiarity with open-source contribution practices.
  • Experience working in startups/early-stage companies.

Compensation & Location

  • Full-time role in Los Angeles, CA, USA (company also has presence in San Francisco, CA).
  • Compensation not specified; equity participation is typical for this VC-backed early-stage company.
  • Visa sponsorship is not available.

About Clera

Clera is an early-stage, venture-backed AI infrastructure company focused on building production-ready, Kubernetes-based systems for GPU-intensive workloads. Its platform helps customers move from bare metal to fully operational AI clusters quickly, enabling large-scale AI inference, training, and cluster operations.

Scraped 8/6/2026