דרושים Human Resources Specialist New College Grad Rotation Program - ב-אנבידיה ב-China, Shanghai

What you’ll be doing:

• Work with architects and performance architects to develop an energy-efficient GPU.

• Develop methodologies and workflows to select and run a wide variety of workloads to train models using ML and/or statistical techniques.

• Develop methodologies to improve the accuracy of energy models under various constraints, such as, process, timing, floorplan and layout.

• Correlate the predicted energy from models created at different stages of the design cycle, with the goal of bridging early estimates to silicon.

• Develop tools to debug energy inefficiencies observed in various workloads run on silicon, RTL and architectural simulators. Work with architects to fix the identified energy inefficiencies.

• Work with performance, verification and emulation methodology and infrastructure development teams to integrate energy models into their platforms.

• Prototype new architectural features, create an energy model, and analyze the system impact.

What we need to see:

• MS degree with 1 year experience in related fields or equivalent experience

• Strong coding skills, preferably in Python, C++.

• Background in machine learning, AI, and/or statistical modeling.

• Interest in computer architecture and energy-efficient GPU designs.

• Familiarity with Verilog and ASIC design principles is a plus.

• Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.

• Desire to bring quantitative decision-making and analytics to improve the energy efficiency of our products.

• Good verbal/written English and interpersonal skills.

What you'll be doing:

• Use internally developed tools and industry standard pre-silicon gate-level and RTL power analysis tools, to help improve product power efficiency.

• Develop and share best practices for performing pre-silicon power analysis, Enhance internal power tools and automate best practices

• Perform comparative power analysis, to spot trends and anomalies, that warrant more scrutiny.

• Interact with architects and RTL designers to help them interpret their power data and identify power bugs; drive them to implement fixes.

• Select and run a wide variety of workloads for power analysis, Collaborate with performance and architecture teams to validate performance of the workloads

• Prototype a new architectural feature in Verilog and analyze power.

What we need to see:

• EE, MS or PhD in related fields, or equivalent experience.

• Basic understanding of concepts of energy consumption, estimation, and low power design.

• Familiarity with Verilog and ASIC design principles, including knowledge of logic cells.

• Good verbal/written English and interpersonal skills; much collaboration with design teams is expected.

• Strong coding skills, preferably in Python, C++.

• Ability to formulate and analyze algorithms, and comment on their time complexity and memory consumption.

• Desire to bring data-driven decision-making and analytics to improve our products.

Ways to stand out from the crowd:

• Familiar with the power tools/flow development is a big plus

Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time — the era of AI has begun. Image recognition and speech recognition — GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. The GPU started out as the engine for simulating human creativity, conjuring up the amazing virtual worlds of video games and Hollywood films.

What you will be doing:

• Study and develop cutting-edge 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.

• 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.

• Some travel is required for conferences and for on-site visits with customers.

What we need to see:

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

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

• Strong verbal and written communication skills in English and organization skills, with a logical approach to problem solving, time management, and task prioritization skills

Join NVIDIA, where our groundbreaking advancements in computer graphics, PC gaming, and accelerated computing have set the standard for over 25 years. As a Developer Technology Engineer, you will be part of an exceptionally experienced team dedicated to pushing the boundaries of AI and computing. This role is an outstanding opportunity to build the next era of technology in a dynamic and innovative environment.

What you'll be doing:

• Understand the responsibilities associated with embodied AI and strive to enhance them.

• Develop on frameworks like IsaacSim and Isaac Lab, ensuring flawless performance.

• Profile and investigate the performance of optimized code together with our internal team.

• Discuss your approach and results with NVIDIA engineers to continuously improve processes.

• Optimize GPU-based physics simulator performance for world-class results.

• Collaborate closely with architecture, research, libraries, tools, and system software teams to invent and develop next-generation architectures, software platforms, and programming models.

What we need to see:

• Bachelor's degree in Computer Science, Robotics, Engineering, or a related field, or equivalent experience.

• Experience with C++, CUDA, Python, and Linux.

• Proven experience with one or more physics simulators such as MuJoCo, Isaac Sim, PyBullet, Drake, or Gazebo.

• Strong communication skills and the ambition to grow and learn about building machine learning applications, optimization, and software engineering.

• Prior involvement with embodied AI or a history at humanoid robotics firms with a focus on physics simulation.

What you'll be doing:

• Developing and introducing groundbreaking reinforcement learning algorithms tailored for LLM applications.

• Collaborating with a world-class team of engineers and researchers to integrate these algorithms into applied scenarios.

• Using your extensive expertise in math and AI to improve the reasoning capabilities of our models.

• Engaging in rigorous testing and refinement processes to ensure flawless performance and reliability.

• Contributing to our collective goal of delivering industry-leading AI solutions, strictly adhering to NVIDIA's high standards.

What we need to see:

• Masters or PhD or equivalent experience in relevant discipline (CE, CS&E, CS, AI)

• Proficient in C++/Python programming.

• Proven experience in reinforcement learning and its application to large language models.

• Strong background in mathematics and AI algorithms, with a focus on reinforcement learning.

• Demonstrated history of applying reinforcement learning algorithms in practical scenarios.

• Understanding of GPU architecture is a huge plus.

• Excellent problem-solving skills and the ability to work collaboratively in a dynamic team environment.

• A passion for innovation and a dedication to achieving outstanding results.

What you'll be doing:

• Help design, develop, and improve scalable infrastructure to support the next generation of AI applications, including copilots and agentic tools.
• Drive improvements in architecture, performance, and reliability, enabling teams to bring to bear LLMs and advanced agent frameworks at scale.
• Stay informed of the latest advancements in AI infrastructure and contribute to continuous innovation.

What we need to see:

• Pursuing a Bachelor's degree or higher in Computer Science or other related field.
• Experience with Python (required) and JavaScript,
• Knowledge of software engineering principles, OOP/functional programming, and writing high-performance, maintainable code.
• Practical experience in AI, machine learning, or agent frameworks (e.g., LangChain, OpenAI Functions).
• Exposure to microservices, web apps, or databases (SQL/NoSQL), containers (Docker), Kubernetes, or CI/CD pipelines, distributed messaging systems (e.g., Kafka) or event-driven architectures.
• Excellent communication skills and a collaborative, proactive approach.

What you'll be doing:

• Develop production-quality software that ships as part of NVIDIA's AI software stack, including optimized large language model (LLM) support.

• Analyze the performance of important workloads, tuning our current software, and proposing improvements for future software.

• Work with cross-collaborative teams of deep learning software engineers and GPU architects to innovate across applications like generative AI, autonomous driving, computer vision, and recommender systems.

• Adapt to the constantly evolving AI industry by being agile and excited to contribute across the codebase, including API design, software architecture, performance modeling, testing, and GPU kernel development.

What we need to see:

• M.S. degree in computer science (or similar) or equivalent experience.

• 2+ years of relevant work or research experience.

• Strong programming skills in C/C++ development, work experience with CUDA development, and familiarity with Python.

• Good understanding of linear algebra.

• Familiarity with the latest trends in machine learning.

• Experience designing high level software architecture.

• Good problem solving skills, including applications of algorithms and data structures.

• Experience with performance analysis, profiling, and code optimization

Ways to stand out from the crowd:

• GPU programming and optimization expertise (e.g. CUDA or OpenCL).

• Practical experience with machine learning, especially deep learning.

• Experience with computer architecture and building performance models for CPUs, GPUs, or other accelerators.

• Familiar with MLIR development and compiler optimization