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Nscale is the Hyperscaler engineered for AI.
Head of Infrastructure Support
Location
Worldwide
Posted
8 days ago
Salary
12 / year
Seniority
Lead
Job Description
Head of Infrastructure Support
Nscale
Role Description At Nscale, you'll find a collaborative, supportive, and innovative environment where your contributions spark real impact. We're building something extraordinary, and we want you at the core. What You'll Be Doing - People Management & Team Leadership - Own day-to-day people management for the Infrastructure US team. - Manage, coach, and mentor team members to deliver high-quality support and right-first-time resolution. - Conduct regular 1:1s, performance reviews, and development planning. - Set and monitor individual and team objectives, driving accountability and continuous improvement. - Manage shift planning, rota coverage, and on-call scheduling. - Identify skills gaps and drive upskilling through training, mentoring, and knowledge sharing across teams. - Ensure roles, responsibilities, and expectations are clearly understood and consistently applied. - Ticket & Service Management - Own ticket queue management, ensuring accurate prioritisation and timely resolution. - Monitor team productivity and workload trends, addressing bottlenecks to maintain service levels. - Ensure adherence to ITIL processes across incidents, requests, changes, and problem management. - Maintain accurate reporting on ticket status, SLA adherence, and team performance for the Infrastructure Support Manager. - Operational Excellence & Continuous Improvement - Identify regional risks and escalate priorities to the Infrastructure Support Manager where required. - Improve dashboards, alerting, and runbooks to reduce repeat incidents and drive self-service resolution. - Maintain consistent standards, processes, and documentation across the regional teams. - Ensure compliance with audit, security, and operational requirements. - Technical Contribution & Support - Work alongside Senior Engineers on complex incidents, technical improvements, and operational tooling. - Provide hands-on support across compute, storage, and networking layers. - Support Kubernetes environments and Linux-based infrastructure at scale. - Contribute to scripting and automation to improve operational workflows. - Travel to Nscale or customer sites when needed to provide technical support. - Incident Management & Stakeholder Interaction - Act as the escalation point for complex or high-impact incidents including on-call (regional). - Lead post-incident reviews, identify recurring patterns, and ensure follow-up actions are tracked and delivered. - Contribute to readiness and support planning for new services, deployments, and projects. Qualifications - Adaptable to customer-driven demands, including out-of-hours support and travel for onsite technical work. - Disciplined, organised, and self-motivated, with the ability to lead, mentor, and support engineers in a fast-paced environment. - Strong leadership mindset with a bias for decisive action, accountability, and continuous improvement. - Experience leading or managing engineers in an operational support environment, including performance, development, and day-to-day team oversight. - Experience owning team workload, prioritisation, and service delivery to meet SLAs. - Excellent communication and interpersonal skills, able to work effectively across all levels of the organisation. - Solid understanding of datacentre technologies (servers, networking, storage, virtualisation) within an operational support context. - Strong Linux systems engineering experience, with proven troubleshooting across compute, storage, and network layers in production. - Experience operating and debugging Kubernetes environments and distributed systems. - Strong networking fundamentals (L2/L3, routing, VLANs, load balancing), with awareness of high-performance fabrics (RDMA/NVLink). - Experience with observability, monitoring, and incident response, including driving issues to resolution and contributing to post-incident improvements. - Familiarity with SRE practices, including runbooks, process improvement, and reducing manual intervention. - Experience with scripting and automation (Bash, Python, or similar) and Infrastructure as Code tools (e.g. Ansible, Terraform). - Strong analytical and problem-solving skills, with the ability to perform deep-dive investigations and root cause analysis. - Familiarity with cloud infrastructure and virtualisation technologies; OpenStack experience preferred. - Understanding of ITIL processes (incident, problem, and change management). Nice to Have - Experience with GPU platforms (NVIDIA/AMD) and performance diagnostics (e.g. nvidia-smi, NCCL). - Exposure to HPC or distributed workloads (e.g. RDMA, InfiniBand, MPI). - Experience with CI/CD or GitOps tooling. - Experience working in multi-region environments. Benefits - Highly competitive package (base + equity) with reviews every 12 months. - Expect a dynamic progression plan tailored to your ambitions. - Human-First Flexibility: We treat you as humans first. Our flexible workplace trusts Nscalers to deliver, giving you the autonomy to shape your day around life's moments. - Join our thriving remote-first team. Geography is no barrier to impact or connection. Equal Opportunities Statement At NScale, we are committed to fostering an inclusive, diverse, and equitable workplace. We believe that a variety of perspectives enriches our work environment, and we encourage applications from candidates of all backgrounds, experiences, and abilities. We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds. If there’s anything we can do to accommodate your specific situation, please let us know.
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Senior AI Infrastructure, Platform Operations Engineer
MirantisStrategic open source infrastructure for containers and virtual machines.
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Role Description Build and maintain scalable AI infrastructure, enabling teams to run ML experiments, deploy machine learning models, and implement MLOps pipelines for production-grade AI. - Design distributed training pipelines for large-scale machine learning and deep learning models. - Optimize compute and storage resources for cloud-based AI/ML workloads on AWS, GCP, or Azure. - Collaborate with data scientists and ML engineers to deploy models in production efficiently. - Implement monitoring, logging, and alerting for model performance and AI workflows. - Ensure scalable, maintainable, and reliable AI infrastructure to support real-time and batch ML applications. Qualifications - 5+ years in Python and ML infrastructure. - Experience in cloud AI platforms (AWS Sagemaker, GCP AI Platform, Azure ML). - Experience with containerization (Docker), orchestration (Kubernetes), and CI/CD for ML. - Experience with distributed systems, data pipelines, and high-performance computing for AI. - Hands-on with deep learning frameworks like TensorFlow or PyTorch.
