Staff Engineer, Inference Optimizations

🕒 October 31

🤠 Texas – Remote

🤠 Texas – Remote

💵 $191.2k - $239k / year

⏰ Full Time

🔴 Lead

🧑‍💻 Full-stack Engineer

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DigitalOcean

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

☁️ SaaS

SaaS • Cloud Computing

DigitalOcean is a cloud infrastructure provider that offers a suite of products and services for developers to build, deploy, and scale applications. Their platform provides comprehensive tutorials, reference material, and support documentation to assist users in managing resources effectively using their API and CLI tools. With features like Droplets (virtual machines), managed databases, Kubernetes, and a marketplace for third-party applications, DigitalOcean focuses on simplicity and performance. They cater to both individual developers and larger organizations looking for cloud solutions that are easy to implement and manage.

📋 Description

• Lead the technical strategy for benchmarking and performance optimizations at the inference engine and GPU kernel layers • Engineer solutions for complex performance issues involving attention-layer optimization, memory and precision management, and advanced parallelization across multi-node GPU clusters • Implement cutting-edge optimization techniques for generative AI inference • Improve batch-size performance using AMD’s AITER library for AMD MI355X and tune CK or ASK kernels for FP8 and BF16 • Identify kernel-fusion opportunities for GLM-5 Transformer-block layers, including FlashAttention and RMS Norm • Tune expert-gateway router kernels for MoE models such as Qwen3-235B, DeepSeek V3, and GLM-5 • Advise on modern NVIDIA and AMD GPU hardware, software integration, and procurement • Develop and deploy quantization techniques including FP8, INT8, and FP4 • Lead code and design reviews and provide technical mentorship without direct-management responsibilities • Partner with Product Management and TPMs to translate hardware limits into shippable product features • Contribute to and integrate open-source AI while maintaining a presence in GPU infrastructure and model-performance communities

🎯 Requirements

• 5+ years of experience in high-performance computing or AI infrastructure • Proven track record of solving compute utilization and memory bandwidth bottlenecks • Deep familiarity with the Gen AI landscape, including LLM, VLM, and LMM model families • Hands-on experience with attention-layer optimizations and parallelization strategies across distributed GPU environments • Comprehensive understanding of NVIDIA and AMD GPU architectures and software ecosystems, including CUDA and ROCm • Extensive experience integrating, building with, and contributing to open-source software projects • Excellent system design skills related to low-level GPU programming, optimization, memory access patterns, and parallel execution • Experience acting as a technical lead and driving design and delivery through cross-functional alignment and expert-level delegation • Deep understanding of GPU architectures, including SMs, Warp scheduling, and Tensor Cores • Expert-level Triton or CUDA proficiency • Experience contributing to the Triton compiler or writing custom CUDA kernels for a major LLM is desired by the posting’s wording

🏖️ Benefits

• Reimbursement for relevant conferences, training, and education, subject to company policy • Flexible time off • Local team meetups • Mental health and well-being support • Eligible employees may receive equity compensation, including a new hire equity grant • Opportunity to participate in DigitalOcean’s Employee Stock Purchase Program in participating countries • Eligibility to participate in DigitalOcean’s annual bonus plan • Remote work arrangement

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