> Markdown version of [/jobs/ext/3190808-cloud-acceleration-engineer-dpu-ai-infra-expiring-soon](https://www.wearedevelopers.com/jobs/ext/3190808-cloud-acceleration-engineer-dpu-ai-infra-expiring-soon). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Cloud Acceleration Engineer - DPU & AI Infra Expiring soon

- **Company:** BYTEDANCE INC.
- **Location:** San Jose, CA, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $162,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cloud Computing, Nvidia CUDA, Computer Networks, Computer Engineering, Software Debugging, Linux, Distributed Computing Environment, Distributed Data Store, Distributed Systems, Field-Programmable Gate Array (FPGA), Network Architecture, Network Virtualization, Network Protocols, Performance Tuning, Remote Direct Memory Access, Software Engineering, Software Systems, Virtual Switching, Network Switches, Data Processing, Graphics Processing Unit (GPU), Application Specific Integrated Circuits, Information Technology, Low Latency, Hardware Acceleration, Machine Learning Operations, Hardware Infrastructure, Service Stack
- **Published:** September 1, 2026
- **Apply:** https://www.gamesjobsdirect.com/job/bytedance/cloud-acceleration-engineer-dpu-ai-infra/350468

## About the Role

Minimum Qualifications - B.S./M.S. in Computer Science, Computer Engineering, or related fields; or Ph.D. with strong research/publications. - 2+ years of relevant industry experience (exception for Ph.D. with strong background). - Proficiency in C/C++ development and debugging. - Strong Linux systems development experience. - Solid understanding of compute, network architecture, and operating systems. - Background in at least one of: software-hardware co-design, distributed systems, high-performance networking, or AI/ML systems. Preferred Qualifications - Ph.D. in related fields with research training and publications. - Experience with software-hardware co-design (networking, storage, or distributed compute). - Hands-on experience with network virtualization (OVS, SR-IOV, eBPF). - Familiarity with DPDK and high-performance user-space networking. - Bonus points for hardware acceleration experience, FPGA/ASIC/GPU/CUDA - Bonus points for experience with NCCL Collectives along
with AI communication patterns and parallelization techniques - Proven experience designing and building AI/ML infrastructure related but not limited to inference kv cache system, data preprocessing system.

## Description

About the Team The ByteDance DPU (Data Processing Unit) team is building the foundational computing infrastructure for ByteDance and Volcano Engine Public Cloud. Our mission is to advance the architecture, development, and research of next-generation software-hardware technologies across compute, networking, and storage for cloud and AI computing. Our technology stack spans - Cloud virtualization & hypervisors - High-performance user-space network protocols (DPDK, RDMA, etc.) - High-speed interconnect and virtual switching - Distributed storage acceleration - GPU virtualization and scheduling for AI/ML workloads We work at the intersection of software systems, distributed infrastructure, and custom hardware acceleration, shaping the next wave of cloud-scale computing. Responsibilities - Design and develop DPU network software with a focus on high performance, low latency, and reliability. - Collaborate with hardware teams to build software-hardware co-design solutions for
networking and storage acceleration. - Explore AI/ML infrastructure acceleration, leveraging DPUs, GPUs, and custom hardware to optimize distributed training and inference. - Drive end-to-end performance optimization, from OS kernels and drivers to user-space runtime systems. - Contribute to architecture design, technical proposals, and long-term research directions.


## Related Videos

- [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia)
- [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops)
- [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load)
- [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker)
- [A Deep Dive on How To Leverage the NVIDIA GB200 for Ultra-Fast Training and Inference on Kubernetes](https://www.wearedevelopers.com/videos/1625-a-deep-dive-on-how-to-leverage-the-nvidia-gb200-for-ultra-fast-training-and-inference-on-kubernetes)
- [The weekly developer show: Boosting Python with CUDA, CSS Updates & Navigating New Tech Stacks](https://www.wearedevelopers.com/videos/1293-the-weekly-developer-show-boosting-python-with-cuda-css-updates-navigating-new-tech-stacks)

## Related Articles

- [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers)
- [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud)
- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix)
- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence)