Job description

Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you’ll find your place here. We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world. DigitalOcean is seeking a Senior Engineer 2 to play a key technical role in our AI Inference Optimization team. DigitalOcean aims to be the Inference Cloud of choice for digitally native companies and you will help ensure we can offer the industry-leading performance for our inference services. You will be responsible for the architectural decisions that maximize throughput and minimize latency for the world’s most advanced large models. As an IC leader, you will act as a force multiplier for the engineering organization, solving the most complex bottlenecks in memory bandwidth and compute utilization while guiding the technical roadmap for our high-performance inference fleet. What You’ll Do: Performance Architecture: Lead the technical strategy for benchmarking and performance optimizations at the inference engine and GPU kernel layers, ensuring our infrastructure extracts maximum value from every TFLOP. Deep-Dive Optimization: Engineer solutions for complex performance issues, including attention layer optimizations, memory and precision management, and advanced parallelization across multi-node GPU clusters. Technological Innovation: Proactively implement cutting-edge optimization techniques to keep DigitalOcean at the forefront of the Gen AI landscape. Some examples of projects you may work on: Improving batch size performance using AMD's AITER library for AMD MI355X - identify and tune AITER's CK (composable kernel) or ASK (assembly) to optimize FP8 / BF16 Identify kernel fusion opportunities for GLM-5 kernels for different layers of the Transformer block (FlashAttention, RMS Norm) Tune expert gateway router kernels for MoE models like Qwen3-235B, DeepSeek V3, GLM-5 etc Hardware & Ecosystem Mastery: Act as the subject matter expert on modern GPU families (NVIDIA/AMD) and their software stacks (CUDA, ROCm, TensorRT, OpenAI Triton), advising on hardware procurement and software integration. Precision Optimization: Develop and deploy state-of-the-art quantization techniques (FP8, INT8, and experimental FP4 ) to double throughput without losing accuracy. Technical Mentorship: Lead by example through high-quality code and design reviews, elevating the technical bar for the team without the administrative overhead of direct management. Strategic Collaboration: Partner with Product Management and TPMs to translate "theoretical hardware limits" into "shippable product features," ensuring our platform is both powerful and developer-friendly. Community Leadership: Maintain a strong presence in the GPU infrastructure and model performance optimization communities, contributing to and integrating the best of open-source AI. What You’ll Bring to DigitalOcean: Technical Depth: 5+ years of experience in high-performance computing or AI infrastructure, with a proven track record of solving compute utilization and memory bandwidth bottlenecks. Gen AI Literacy: Deep familiarity with the Gen AI (LLM, VLM, LMM) landscape, including the specific quirks and architectural requirements of major model families. Optimization Expert: Hands-on experience with attention-layer optimizations and parallelization strategies across distributed GPU environments. Hardware Fluency: Comprehensive understanding of NVIDIA and AMD GPU architectures and their respective software ecosystems (CUDA, ROCm, etc.). Open Source Mastery: Extensive experience integrating, building with, and contributing to open-source software projects. Systems Design: Excellent system design skills, particularly related to low-level GPU programming - optimization, memory access patterns, and parallel execution. Leadership through Influence: Experience acting as a technical lead, driving design and delivery through cross-functional alignment and expert-level delegation. Low-Level Mastery: Deep understanding of GPU architectures (SMs, Warp scheduling, Tensor Cores). The Toolkit: Expert-level Triton or CUDA. If you’ve contributed to the Triton compiler or wrote custom CUDA kernels for a major LLM, we want you. Compensation Range: $191,200 - $239,000 *This is a remote role JR: 2026-7625 #LI-Remote Why You’ll Like Working for DigitalOcean We innovate with purpose. You’ll be a part of a cutting-edge technology company with a high-growth trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As part of our team, you’ll embody our "Shark" mindset: bold, ambitious, and scrappy. You'll lead with a bias for action and take true ownership of our products, customer success, and team culture. We prioritize career development. At DigitalOcean, you’ll do the best work of your career. You will join a community of exceptional talent, collaborating closely with some of the brightest and most interesting people in the industry. We are a high-performance and fast-paced organization that will always challenge you to think big. Our talent development team prioritizes your professional development and provides resources to support your growth. We provide employees with reimbursement for relevant conferences, training, and education, subject to company policy. We care about your well-being. We take a comprehensive approach to our total rewards packages because we know different things drive different people. Our benefits are designed to support you and may include flexible time off, local team meetups, and mental health and well being support. Our benefits philosophy is consistent globally, but specific benefits and eligibility vary by location to reflect local needs and regulations. We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. Eligible employees may also receive equity compensation, which may include a new hire equity grant and, in participating countries, the opportunity to participate in our Employee Stock Purchase Program. Equity awards are subject to approval and the terms of the applicable plan. Non-sales roles : In addition to base salary, this role is eligible to participate in DigitalOcean’s annual bonus plan and may be eligible for a new hire equity grant, subject to plan terms and local eligibility. Bonus amounts depend on company and individual performance. Sales roles (sales compensation eligible) : In addition to base salary, this role may be eligible to earn incentive compensation under the applicable sales compensation plan and may be eligible for a new hire equity grant, subject to plan terms and local eligibility. DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, sex, disability, protected veteran status, or any other characteristic protected by applicable law. Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.

Requirements

Must-haves

Performance Architecture: Lead the technical strategy for benchmarking and performance optimizations at the inference engine and GPU kernel layers, ensuring our infrastructure extracts maximum value from every TFLOP.
Deep-Dive Optimization: Engineer solutions for complex performance issues, including attention layer optimizations, memory and precision management, and advanced parallelization across multi-node GPU clusters.
Technological Innovation: Proactively implement cutting-edge optimization techniques to keep DigitalOcean at the forefront of the Gen AI landscape. Some examples of projects you may work on:
Improving batch size performance using AMD's AITER library for AMD MI355X - identify and tune AITER's CK (composable kernel) or ASK (assembly) to optimize FP8 / BF16
Identify kernel fusion opportunities for GLM-5 kernels for different layers of the Transformer block (FlashAttention, RMS Norm)
Tune expert gateway router kernels for MoE models like Qwen3-235B, DeepSeek V3, GLM-5 etc
Precision Optimization: Develop and deploy state-of-the-art quantization techniques (FP8, INT8, and experimental FP4 ) to double throughput without losing accuracy.
Technical Mentorship: Lead by example through high-quality code and design reviews, elevating the technical bar for the team without the administrative overhead of direct management.
Strategic Collaboration: Partner with Product Management and TPMs to translate "theoretical hardware limits" into "shippable product features," ensuring our platform is both powerful and developer-friendly.
Community Leadership: Maintain a strong presence in the GPU infrastructure and model performance optimization communities, contributing to and integrating the best of open-source AI.
Technical Depth: 5+ years of experience in high-performance computing or AI infrastructure, with a proven track record of solving compute utilization and memory bandwidth bottlenecks.
Gen AI Literacy: Deep familiarity with the Gen AI (LLM, VLM, LMM) landscape, including the specific quirks and architectural requirements of major model families.
Optimization Expert: Hands-on experience with attention-layer optimizations and parallelization strategies across distributed GPU environments.
Hardware Fluency: Comprehensive understanding of NVIDIA and AMD GPU architectures and their respective software ecosystems (CUDA, ROCm, etc.).
Open Source Mastery: Extensive experience integrating, building with, and contributing to open-source software projects.
Systems Design: Excellent system design skills, particularly related to low-level GPU programming - optimization, memory access patterns, and parallel execution.
Leadership through Influence: Experience acting as a technical lead, driving design and delivery through cross-functional alignment and expert-level delegation.
Low-Level Mastery: Deep understanding of GPU architectures (SMs, Warp scheduling, Tensor Cores).
The Toolkit: Expert-level Triton or CUDA. If you’ve contributed to the Triton compiler or wrote custom CUDA kernels for a major LLM, we want you.
$191,200 - $239,000
This is a remote role
#LI-Remote Why You’ll Like Working for DigitalOcean
DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, sex, disability, protected veteran status, or any other characteristic protected by applicable law.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aillm

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Pto

Professional Development