Top Tech Jobs & Startup Jobs

Support ML engineers running large-scale training and inference workloads across Kubernetes, cloud, and GPU infrastructure. Diagnose distributed PyTorch, CUDA, networking, storage, scheduling, performance, and reliability issues. Analyze observability data, guide customers through complex infrastructure problems, support production incidents, and improve platform reliability through automation, tooling, documentation, runbooks, and operational processes. The role partners closely with infrastructure, networking, and platform engineering teams in a hybrid office environment.

Lead and scale an enterprise Account Executive team selling AI infrastructure, developer platforms, compute, and related solutions. Own pipeline generation, forecasting, deal inspection, quota attainment, territory planning, and enterprise sales methodology. Coach sellers through complex technical sales involving ML, infrastructure, engineering, procurement, finance, and executive stakeholders. Build repeatable go-to-market processes, partner cross-functionally, shape product positioning, recruit talent, and develop the enterprise sales playbook.

Design and scale reliable spine-leaf data center networks supporting GPU clusters and AI workloads. Build Ethernet fabrics using EVPN/VXLAN and BGP, optimize traffic, support RoCE/RDMA, and manage backbone, WAN, DCI, and edge connectivity. Develop network automation and Infrastructure-as-Code solutions, improve observability and telemetry, troubleshoot distributed performance issues, and collaborate with compute, storage, platform, and operations teams. The role requires hands-on Cumulus NOS expertise and experience with large-scale, high-performance infrastructure.

Own global talent acquisition strategy for an AI infrastructure company. Build and lead the recruiting team, systems, processes, employer brand, sourcing strategy, interview practices, and hiring analytics. Partner with technical and executive leaders on workforce planning and global hiring across AI/ML, software engineering, infrastructure, and data center functions. Ensure compliant, scalable recruiting across multiple countries while maintaining speed and high hiring standards.

Develop and scale the Lightning AI platform’s frontend and UI infrastructure using React and Redux. Build end-to-end features, improve stability and performance, evaluate technical architecture, automate software delivery, reduce technical debt, and mentor engineers. Collaborate with engineering, product, and design teams in a rapidly changing SaaS environment while maintaining high standards for code quality and system design.

Support ML engineers operating production training and inference workloads across Kubernetes, cloud, and GPU infrastructure. Diagnose distributed PyTorch, CUDA, NCCL, networking, storage, scheduling, and performance issues; analyze observability data; advise customers during incidents; and improve reliability through automation, tooling, documentation, runbooks, and operational processes. The role is remote in the Philippines or Singapore and follows a Sunday-Wednesday APAC shift.