DevOps Engineer | SDE - 1 | SDE  - 2

Role: Senior GPU Platform Engineer

Function: Infrastructure Engineering

Location: Singapore

Type: Full-time

Industry: Cloud Infrastructure, AI/ML, Enterprise Software

About Company

A deeptech startup developing an AI-native private cloud platform. The company automates orchestration, security, compliance, and workload management for enterprise environments.

Based in Bangalore with a team of 30 talented professionals. Backed by $9.6 million in seed funding from RTP Global.

Position Overview

You'll architect and optimize GPU infrastructure for an AI-native cloud platform that powers enterprise workloads at scale. You'll build next-generation cloud infrastructure from the ground up while working with cutting-edge GPU technologies. This role offers high ownership in designing distributed systems that handle large-scale GPU computing environments for performance, reliability, and cost efficiency.

Role & Responsibilities

• Design and implement scalable GPU infrastructure systems for AI workloads and high-performance computing environments
• Optimize distributed GPU computing environments for performance, reliability, and cost efficiency at enterprise scale
• Build monitoring, orchestration, and automation tools for large-scale GPU performance
• Develop infrastructure APIs and services for intelligent GPU resource allocation and workload scheduling
• Collaborate with global platform teams to integrate GPU resources with cloud orchestration systems
• Drive technical excellence in GPU platform architecture and distributed systems design patterns
• Implement performance optimization strategies for compute-intensive AI and ML workloads across hybrid cloud environments

Must Have Criteria

• 5-12 years of software engineering experience in HCP, network infrastructure, or cloud platforms
• Hands-on experience with GPU infrastructure management and optimization (NVIDIA CUDA, A100/H100, or Google TPUs)
• Proven experience building distributed systems handling 100K+ concurrent sessions or 30M+ monthly active users
• Strong programming skills in systems languages (Go, Java, Python, or Rust) with focus on performance optimization
• Production experience with container orchestration platforms (Kubernetes, Docker) and microservices architecture
• Experience at hyperscale technology companies (Meta, Google, AWS, Microsoft, Grab, GoTo, Traveloka)
• Proven track record of leading technical initiatives or mentoring engineering teams in infrastructure domains

Nice to Have

• Deep experience with NVIDIA GPU architectures (V100, A100, H100) and CUDA optimization techniques
• Knowledge of GPU cluster management and distributed training frameworks (Horovod, DeepSpeed, Ray)
• Experience with high-performance networking (InfiniBand, RDMA) for GPU clusters and data center interconnects
• Familiarity with GPU virtualization technologies (NVIDIA MIG, vGPU) and multi-tenancy solutions
• Experience with performance profiling and optimization tools for GPU workloads (Nsight, NVPROF)

What We Offer

• Opportunity to build cutting-edge AI-native cloud infrastructure from scratch with global impact
• High ownership and technical leadership in a fast-growing deeptech startup backed by top-tier VCs
• Work with seasoned tech veterans and industry experts on globally relevant engineering challenges
• Competitive compensation package with significant equity upside in a high-growth startup
• Flexible work environment with access to latest GPU technologies and cloud infrastructure tools