位于上海市的 18 个优质stack engineer职位（正在招聘！）

Deep Learning Compiler CI/Infrastructure Engineer
NVIDIA —上海市
- 全职
Test Automation Engineer (In-Vehicle Infotainment)
Luxoft —上海市
Senior Director, Compiler Engineering
NVIDIA —上海市
- 全职
COUNTRY ENGINEERING & DEVELOPMENT DESIGN PROFESSIONAL -
OPmobility —上海市
ADAS Algorithm Engineer – Plan & Control Evaluation 智驾规控算法评测算法工程师
Mercedes-Benz Group AG —上海市
13 小时
Advanced Manufacturing Engineer - Watch
Apple —上海市
Design Manager
Stack Modular —上海市
快速申请
Automotive Ethernet and RCP Expert FAE
onsemi —上海市
- 全职
6天
Operations Engineer
JLL —上海市
4天
Senior Data Engineer, Amazon Global Selling -AIT
Amazon (Shanghai) International Trading Company Limited —上海市
- 全职
13天
Customer Quality Engineer
Lenovo —上海市
12天
SW Development Engineer: System RF Data Ecosystem
Apple —上海市
2天
Product Engineer
GRAMMER AG —上海市
AI Framework Eng.
Advanced Micro Devices, Inc —上海市
Senior Manager, SRE
Tapestry Inc —上海市
- 全职
Senior Site Reliability Engineer - ASE / iCloud
Apple —上海市
4天
Advisory Engineer, Google expert m/f/d
Lenovo —上海市
- 全职
Data Consultant Manager
EPAM Systems, Inc. —上海市

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Test Automation Engineer (In-Vehicle Infotainment)
Luxoft —上海市
Proactive in proposing improvements to test methodologies and toolchains. Improve & Automate: Contribute to test automation initiatives, develop scripts to…

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Deep Learning Compiler CI/Infrastructure Engineer

NVIDIA -
上海市

立即申请

职位详情

全职

完整职位描述

NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”.
In this role you will work closely with deep learning compiler engineers to own and evolve the CI/CD infrastructure that powers the development lifecycle of NVIDIA's deep learning compiler stacks. Responsibilities include designing and operating scalable CI systems that orchestrate ML workloads across diverse GPU and accelerator environments, deliver reliable correctness and performance signals, and serve as a primary technical point of contact for CI health, new project onboarding, and new architecture bring-up.
What you'll be doing:

Build, maintain, and improve CI infrastructure that supports development, verification, and release of NVIDIA’s deep learning compiler stacks across GPU and accelerator environments
Improve CI reliability and signal quality by reducing flakes, improving reproducibility, strengthening diagnostics, and making correctness and performance failures easier to understand and act on
Apply automation, AI, and agent-based workflows to reduce manual CI operations, speed up failure triage, and improve developer efficiency
Build reusable and self-service CI platforms that support multiple products, projects, model suites, hardware targets, and software configurations while partnering closely with compiler, infrastructure, and release teams

What we need to see:

BS, MS, or PhD (or equivalent experience) in Computer Science, Computer/Electrical Engineering, Mathematics, or a related field
5+ years of experience designing, scaling, and operating CI/CD, build/release, or developer infrastructure for complex software systems
Proven experience building CI platforms end-to-end using systems such as GitLab CI, Jenkins, or similar tools, including pipeline orchestration, compute/runner management, artifact and package systems, and observability, with strong emphasis on reliability, reproducibility, and debuggability
Strong software engineering skills (Python required), with the ability to design, implement, and debug distributed systems end-to-end
Familiarity with edge devices (SOC, e.g. NVIDIA Tegra) in host-target architecture, ability to debug it and knowledge to its automation nuances
Proven track record of designing, building, and deploying AI/LLM-based systems in real engineering workflows, demonstrating skill in evaluating trade-offs, failure modes, maintainability, and measurable impact on developer productivity, signal quality, or operational efficiency

Ways to stand out from the crowd:

Experience crafting and shipping sophisticated AI/agent-based systems that improve continuous integration or developer efficiency. These systems include intelligent test selection, automated triage and routing, regression localization, autonomous remediation, and developer-assist workflows
Experience operating CI for DL/GPU software environments, including multi-GPU / multi-node workloads on Slurm, Kubernetes, or cloud platforms
Familiarity with compiler IRs and infrastructure such as LLVM/MLIR, TensorRT IR, especially in the context of testing, debugging, and validating compiler-driven workloads

With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.

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在上海市的stack engineer个职位

Deep Learning Compiler CI/Infrastructure Engineer

Test Automation Engineer (In-Vehicle Infotainment)

Senior Director, Compiler Engineering

COUNTRY ENGINEERING & DEVELOPMENT DESIGN PROFESSIONAL -

ADAS Algorithm Engineer – Plan & Control Evaluation 智驾规控算法评测算法工程师

Advanced Manufacturing Engineer - Watch

Design Manager

Automotive Ethernet and RCP Expert FAE

Operations Engineer

Senior Data Engineer, Amazon Global Selling -AIT

Customer Quality Engineer

SW Development Engineer: System RF Data Ecosystem

Product Engineer

AI Framework Eng.

Senior Manager, SRE

Senior Site Reliability Engineer - ASE / iCloud

Advisory Engineer, Google expert m/f/d

Data Consultant Manager

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