Digital Ocean

1 day ago

Staff Engineer, Inference Optimizations

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Lead performance architecture and deep-dive optimization for DigitalOcean’s AI inference stack, improving throughput and reducing latency across inference engine and GPU kernel layers. Drive benchmarking, kernel-level and attention/memory/precision optimizations, and advanced parallelization for multi-node GPU clusters. Serve as a subject matter expert across NVIDIA/AMD ecosystems (CUDA/ROCm/TensorRT/Triton), guide technical roadmap decisions, and translate hardware limits into shippable, developer-friendly product features.

Location: Boston

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Lead technical strategy for benchmarking and performance optimizations across inference engine and GPU kernel layers.
•Engineer solutions for complex performance issues, including attention layer optimizations, memory/precision management, and parallelization across multi-node GPU clusters.
•Implement cutting-edge optimization techniques for GenAI inference, including batch size performance tuning, kernel fusion, and MoE router kernel tuning.
•Act as subject matter expert on modern GPU families and software stacks, advising on hardware procurement and software integration.
•Provide technical mentorship through high-quality code and design reviews, and collaborate with Product Management and TPMs to ship performance-driven features.

Pay and Benefits

Salary: USD 191,200 - 239,000 annually

Perks:EquityEsppEmployee AssistanceFlexible Time

Key Requirements

•5+ years of experience in high-performance computing or AI infrastructure, with a track record of resolving compute utilization and memory bandwidth bottlenecks.
•Deep familiarity with the Gen AI landscape (LLM, VLM, LMM) and architectural requirements of major 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 their software ecosystems (CUDA, ROCm).
•Expert-level Triton or CUDA, including experience contributing to Triton or writing custom CUDA kernels for major LLMs.

Experience:5+ yearsHigh-performance computingAI infrastructureGenAIOpen sourceGPU optimization

Skills:Technical leadershipCode/design reviewCross-functional collaboration

Languages:English

Tech Stack:GPUNVIDIAAMDCUDAROCmTensorRTOpenAI TritonTriton compilerCUDA kernelsAMD AITERMI355XFP8BF16FP4INT8FlashAttentionRMS NormTransformerMoEExpert gateway router

Company Brief

Digital Ocean

Provides cloud infrastructure and developer-focused cloud services including scalable droplets, managed databases, Kubernetes, object storage, and networking to simplify deploying and managing applications for developers and small-to-medium businesses.

Industry: Cloud Computing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 250M to 500M

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: New York, United States

Founded: 2011

Glassdoor: 3.8

Website LinkedIn

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Digital Ocean

1 day ago

Staff Engineer, Inference Optimizations

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Location: Boston

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Lead technical strategy for benchmarking and performance optimizations across inference engine and GPU kernel layers.
•Engineer solutions for complex performance issues, including attention layer optimizations, memory/precision management, and parallelization across multi-node GPU clusters.
•Implement cutting-edge optimization techniques for GenAI inference, including batch size performance tuning, kernel fusion, and MoE router kernel tuning.
•Act as subject matter expert on modern GPU families and software stacks, advising on hardware procurement and software integration.
•Provide technical mentorship through high-quality code and design reviews, and collaborate with Product Management and TPMs to ship performance-driven features.

Pay and Benefits

Salary: USD 191,200 - 239,000 annually

Perks:EquityEsppEmployee AssistanceFlexible Time

Key Requirements

•5+ years of experience in high-performance computing or AI infrastructure, with a track record of resolving compute utilization and memory bandwidth bottlenecks.
•Deep familiarity with the Gen AI landscape (LLM, VLM, LMM) and architectural requirements of major 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 their software ecosystems (CUDA, ROCm).
•Expert-level Triton or CUDA, including experience contributing to Triton or writing custom CUDA kernels for major LLMs.

Experience:5+ yearsHigh-performance computingAI infrastructureGenAIOpen sourceGPU optimization

Skills:Technical leadershipCode/design reviewCross-functional collaboration

Languages:English

Tech Stack:GPUNVIDIAAMDCUDAROCmTensorRTOpenAI TritonTriton compilerCUDA kernelsAMD AITERMI355XFP8BF16FP4INT8FlashAttentionRMS NormTransformerMoEExpert gateway router

Company Brief

Digital Ocean

Industry: Cloud Computing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 250M to 500M

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: New York, United States

Founded: 2011

Glassdoor: 3.8

Website LinkedIn