About the Role
Bridge GPU/CPU health automation and ML lifecycle management. You’ll automate node health checks and build robust Kubeflow pipelines, ensuring a high-performance environment for AI engineers.
Key Responsibilities
- GPU/CPU Health Automation (Priority #1): Automate health checks during node provisioning (link stability, ECC, PCIe, thermal) and store results in Ground Truth Library; collaborate with GPU Perf Engineering on thresholds.
- Build and maintain end-to-end ML pipelines in Kubeflow (deployment, monitoring).
- Manage Kubernetes clusters with Docker in production.
- Automate CI/CD via GitHub Actions (or GitLab CI/Jenkins).
- Write Python/Bash scripts for Linux systems and infrastructure tasks.
- Implement monitoring/alerting with Prometheus & Grafana (ELK stack a plus).
- Troubleshoot across dev/staging/production; document processes, runbooks, postmortems.
- Ensure security, compliance, and governance in cloud/on-prem environments.
Required Skills & Qualifications
- ~2+ years in MLOps, DevOps, SRE, or infrastructure roles.
- Strong Python and Linux skills.
- Hands-on Kubernetes & Docker in production.
- Experience with CI/CD (GitHub Actions, GitLab CI, or Jenkins).
- Understanding of deep learning pipelines & frameworks (TensorFlow/PyTorch).
- Prometheus & Grafana experience (ELK familiarity a plus).
- Basics of networking, security, system administration, and databases.
- Hardware-level diagnostic concepts (ECC, PCIe errors, thermal, link stability).
- Cloud fundamentals (AWS, GCP, or Azure).
Personal Attributes & Soft Skills
- detail-oriented
- problem-solving & logical thinking
- curious & inquisitive
- teamwork & collaboration
- patience & perseverance
- quick learner, flexible
- responsibility & discipline
- creative & innovative thinking
- Ownership mindset for reliability and outcomes
- Resilience under pressure; R&D experimentation mindset
Nice-to-Have
- SRE practices (SLIs/SLOs, incident response)
- IaC tools (Terraform, Ansible)
- Distributed systems & microservices architecture
- Prior GPU workload or hardware validation exposure
- Kubeflow/MLflow advanced experience
- Relevant certifications (CKA/CKAD, cloud certs)
Benefits
- R&D-driven environment with cutting-edge GPU technologies
- Competitive salary + performance bonus
- Continuous learning, skill-building, and career growth
- Shared individual and organizational development goals