Senior Kubernetes Software Engineer jobs at Nvidia in China, Beijing

You will work directly with founders, engineering leaders, and developer communities buildingThis role is ideal for someone who enjoyshands-on technical engagement, ecosystem building, and communicating complex technology in a clear and compelling way.

You will be a, shaping solution strategy, enabling partners, and helping drive the next generation of AI-powered retail innovation.

• Serve as the trusted technical advisor, and champion for the developer ecosystem in Retail Industry, with multi-functional partners to drive adoption of NVIDIA technologies.

• Help developers leverage NVIDIA’s tools for GenAI and LLMs- including Triton Inference Server, TensorRT-LLM, NeMo Framework, and CUDA-accelerated pipelines —to optimize model performance and scalability.

• Build and deliver sample applications, tutorials, and technical content that highlight best practices for building with LLMs and agentic workflows.

• Partner with solution architects to benchmark improvements and support performance tuning of LLM deployments across NVIDIA platforms.

• Guide startups through integration with NVIDIA’s Gen AI stack and support their certification in NVIDIA partner programs.

• Represent the company at industry events, developer meetups, andhackathons—evangelizingour LLM and Agentic AI strategy to a technical audience.

• Gather developer feedback to inform product and roadmap decisions related to LLM inference, training, and deployment tooling.

• Identify promising Gen AI startups and help them go to market through co-branded solution development and strategic partnerships

• BS or Masters in Computer Science, Engineering, or equivalent practical experience.

• 8+ years in Developer Relations, AI engineering, startup GTM roles, or Technical Alliances.

• Deep hands-on experience with LLMs (e.g., Qwen, Deepseek, LangChain, RAG pipelines) and autonomous agent frameworks.

• Proficiency with Python, containerization tools (Docker, Kubernetes), and Linux-based development environments.

• Understanding of model fine-tuning, prompt engineering, memory architectures, tool use in agent systems, and orchestration frameworks.

• Excellent communication and storytelling skills—comfortable presenting to technical and business audiences.

• Experience in retail AI, Machine Learning and Deep Learning applications

• Familiarity with advanced computing, AI, and/or GPU acceleration platforms (Triton Inference Server, TensorRT-LLM, NeMo Framework, and CUDA-accelerated pipelines).

• Successful history of building and scaling developer communities and delivering impactful technical enablement programs.

What you will be doing:

• Investigate and resolve sensor calibration and egomotion algorithm/toolchain issues across multiple OEM vehicle platforms.

• Develop core autonomous driving functionality for global markets by fusing state-of-the-art perception DNNs with map signals.

• Build real-time 3D world models for planning, integrating diverse inputs from sensors and external sources.

• Develop and optimize LLM, VLM, and VLA systems for autonomous driving applications, including pre-training and fine-tuning.

• Design innovative data generation and collection strategies to improve dataset diversity and quality.

• Collaborate with cross-functional teams to deploy end-to-end AI models in production, ensuring performance, safety, and reliability standards are met.

What we need to see:

• A MS, or PhD, or equivalent professional experience in Computer Science, Computer Engineering, Mathematics, Physics, or a related discipline.

• Over 3 years of relevant industry experience.

• Expertise in C/C++ programming, with a comprehensive understanding of standard C++ features, algorithms, and data structures, along with proficiency in Linux environments.

• In-depth knowledge of parameter models for sensor calibration.

• A solid grasp of digital image processing, three-dimensional multi-view geometry, nonlinear optimization, and KF/EKF.

• A robust mathematical foundation, especially in matrix-related concepts.

• Engineering expertise in developing and delivering deep learning applications for autonomous vehicles or robotics

• Engineering expertise in developing and delivering real-time 3D world models for planning in AV system.

• Excellent collaboration skills and the ability to work effectively with individuals from various nationalities and locations.

Ways to stand out from the crowd:

• Experience with a range of sensors and their data (camera, lidar, radar, IMU, GNSS, CAN Odometry).

• Extensive experience in SLAM algorithms

• Extensive deep learning experience related to autonomous driving.

• A track record of designing SLAM algorithms for successful ADAS projects.

What you will be doing:

• You will work and develop state of the art techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures

• You will provide the best AI solutions using GPUs working directly with key customers

• Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models

What we need to see:

• Pursuing MS or PhD from a leading University in an engineering or Computer Science related discipline

• Strong knowledge of C/C++, software design, programming techniques, and AI algorithms

• Experience with parallel programming, ideally CUDA C/C++

• Good communication and organization skills, with a logical approach to problem solving, time management, and task prioritization skills

Preferred internship duration: 4+ months

We’re working on the next generation of recommendation tools and pushing the boundaries of accelerating model training and inference on GPU. You’ll join a team of ML, HPC and Software Engineers and Applied Researcher developing a framework designed to make the productization of GPU-based recommender systems as simple and fast as possible.

What you’ll be doing

In your role as CUDA Engineer Intern you will be profiling and investigating the performance of optimized code together within our HPC team. Part of this job will be to perform tests, unit tests and validate the numerical performance and correctness of the code. You will discuss your approach and results together with our CUDA engineers.

What we need to see:

• Experience with c++, CUDA, python and Linux.

• Bachelor or Master degree in software engineering or technical field such as mathematics or applied science.

• communication skills

• ambitious to grow and learn about building machine learning applications, optimization and software engineering.

What you’ll be doing:

• Develop and implement solutions throughout software development lifecycles to improve developer efficiency, accelerate feedback loops, and boost release reliability

• Experience designing, developing, and deploying AI agents to automate software development workflows and processes.

• Continuously measure and report on the impact of AI interventions, showing progress in metrics such as cycle time, change failure rate, and mean time to recovery (MTTR).

• Build and deploy predictive models to identify high-risk commits, forecast potential build failures, and flag changes that have a high probability of failures.

• Research emerging AI technologies and engineering best practices to continuously evolve our development ecosystem and maintain a competitive edge.

What we need to see:

• BE (MS preferred) or equivalent experience in EE/CS with 10+ years of work experience.

• Deep practical knowledge of Large Language Models (LLMs), Machine Learning (ML), and Agent development

• Strong background in implementing AI solutions to solve real-world software engineering problems.

• Hands-on experience on Python/Java/Go with extensive python scripting experience.

• Experience in working with SQL/NoSQL database systems such as MySQL, MongoDB or Elasticsearch.

• Full-stack, end-to-end development expertise, with proficiency in building and integrating solutions from the front-end (e.g., React, Angular) to the back-end (Python, Go, Java) and managing data infrastructure (SQL/NoSQL).

• Experience with tools for CI/CD setup such as Jenkins, Gitlab CI, Packer, Terraform, Artifactory, Ansible, Chef or similar tools.

• Good understanding of distributed systems, understanding of microservice architecture and REST APIs.

• Ability to effectively work across organizational boundaries to enhance alignment and productivity between teams.

Ways to stand out from the crowd:

• Proven expertise in applied AI, particularly using Retrieval-Augmented Generation (RAG) and fine-tuning LLMs on enterprise data to solve complex software engineering challenges.

• Experience delivering large-scale, service-oriented software projects under real-time constraints, demonstrating an understanding of the complex development environments this role will optimize.

• Expertise in leveraging large language models (LLMs) and Agentic AI to automate complex workflows, with knowledge of retrieval-augmented generation(RAG) and fine-tuning LLMs on enterprise data.

What you'll be doing:

• Study and develop cutting-edge techniques in CUDA programming, profiling, optimization. Application domains include deep learning, graphic, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures.

• Work directly with key customers to understand the current and future problems they are solving and provide the best AI solutions using GPUs.

• Collaborate closely with the architecture, research, libraries, tools, and system software teams at NVIDIA to influence the design of next-generation architectures, software platforms, and programming models.

What we need to see:

• A degree from university in an engineering or computer science related discipline (BS; MS or PhD preferred).

• Strong knowledge of C/C++, software design, programming techniques, GPU arch, parallel computing, and AI algorithms.

• Prefer solid skills of CUDA C/C++ programming, performance profiling and optimization.

• Prefer expert knowledge of GPU arch.

• Good communication skills.

What you'll be doing:

• Design and implement triggering systems and deploy containerized orchestration pipelines for distributed map creation, maintenance, and evaluation from crowdsourced vehicle data

• Develop map quality detection systems including automated hotspot detection algorithms and human-in-the-loop review workflows for large scale map validation

• Develop Python, C++, and JavaScript tools for map management, data validation, on-vehicle testing, and web-based geospatial visualizations

• Build C++ modules for on-vehicle map integration with perception, localization, and other consumers to ensure end-to-end validation of the maps' impact on driving performance

• Work with embedded systems and real-time constraints to optimize map consumption by autonomous driving software

• Collaborate with perception, planning, and operations teams to improve map quality and real-time driving performance

What we need to see:

• BS or MS degree in Computer Science, Software Engineering, or related field (or equivalent experience)

• 5+ years of proven experience building production data pipelines, distributed systems, mapping infrastructure, or map to vehicle integration

• Strong C++ programming skills for performance-critical algorithms, data processing tools, and on-vehicle software

• Strong Python programming skills for automation, workflow orchestration, and API development

• Proficiency with JavaScript for building web-based tools, visualizations, and internal dashboards

• Hands-on experience with Airflow or similar workflow orchestration frameworks

• Experience with Docker, Kubernetes, and cloud platforms

• Experience with Protocol Buffers, gRPC, and REST API design

• Excellent problem-solving skills and ability to debug sophisticated distributed and embedded systems

Ways to stand out from the crowd:

• Extensive experience with SD & HD mapping and autonomous vehicle software architectures

• Deep understanding of how maps are consumed by localization, perception, and planning systems in autonomous vehicles

• Deep knowledge of road topology generation, analysis, and graph partitioning algorithms

• Experience with computer vision concepts pipelines (3D geometry, point clouds,structure-from-motion,COLMAP, SfM, visual odometry)

• Experience debugging and profiling performance on embedded platforms (NVIDIA Orin, Xavier, etc.)