Spydra - Site Reliability Engineer - DevOps

1 week ago

Hyderabad, India Spydra Full time

We are seeking a highly skilled and self-driven Site Reliability Engineer to join our dynamic team.

This role is ideal for someone with a strong foundation in Kubernetes, DevOps, and observability who can also support machine learning infrastructure, GPU optimization, and Big Data ecosystems.

You will play a pivotal role in ensuring the reliability, scalability, and performance of our production systems, while also enabling innovation across ML and data teams.


Key Responsibilities Automation & Reliability :


- Design, build, and maintain Kubernetes clusters across hybrid or cloud environments (e.g., EKS, GKE, AKS).

- Implement and optimize CI/CD pipelines using tools like Jenkins, ArgoCD, and GitHub Actions.

- Develop and maintain Infrastructure as Code (IaC) using Ansible, Terraform, or & Observability :


- Deploy and maintain monitoring, logging, and tracing tools (e.g., Thanos, Prometheus, Grafana, Loki, Jaeger).

- Establish proactive alerting and observability practices to identify and address issues before they impact users.


ML Ops & GPU Optimization :


- Support and scale ML workflows using tools like Kubeflow, MLflow, and TensorFlow Serving.

- Work with data scientists to ensure efficient use of GPU resources, optimizing training and inference & Incident Management :


- Lead root cause analysis for infrastructure and application-level incidents.

- Participate in the on-call rotation and improve incident response & Automation :


- Automate operational tasks and service deployment using Python, Shell, Groovy, or Ansible.

- Write reusable scripts and tools to improve team productivity and reduce manual Learning & Collaboration :


- Stay up-to-date with emerging technologies in SRE, ML Ops, and observability.

- Collaborate with cross-functional teams including engineering, data science, and security to ensure system integrity and :


- 3+ years of experience as an SRE, DevOps Engineer, or equivalent role.

- Strong experience with Kubernetes ecosystem and container orchestration.

- Proficiency in DevOps tooling including Jenkins, ArgoCD, and GitOps workflows.

- Deep understanding of observability tools, with hands-on experience using Thanos and Prometheus stack.

- Experience with ML platforms (MLflow, Kubeflow) and supporting GPU workloads.

- Strong scripting skills in Python, Shell, Ansible, or :


- CKS (Certified Kubernetes Security Specialist) certification.

- Exposure to Big Data platforms (e.g., Spark, Kafka, Hadoop).

- Experience with cloud-native environments (AWS, GCP, or Azure).

- Background in infrastructure security and compliance.


(ref:hirist.tech)

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