Senior Software Engineer, Profiling Services at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Semiconductor, AI/MLIndustries

Requirements

BS or MS degree or equivalent experience in Computer Engineering, Computer Science, or related field
6+ years of meaningful software development experience in C, C++, and Python
6+ years in system software design, operating systems fundamentals, computer architectures, performance analysis, and delivering production-quality software
Strong interpersonal, verbal, and written communication skills, with ability to build cross-organizational partnerships and lead technical teams through complex challenges
Extensive knowledge of profiling technologies (sampling, tracing), overhead analysis, and diverse profiling data (CPU/GPU events, performance counters, API traces, event correlation); familiarity with existing profiling ecosystems and their limitations is a plus
In-depth knowledge of CUDA APIs, runtime, streams, kernels, and GPU architecture
Familiarity with ML frameworks such as PyTorch and JAX, and knowledge of performance analysis for AI training/inference applications
Experience developing and debugging across complex multi-layered software systems, including user mode and kernel drivers, with proven ability to contribute to and extend substantial codebases (100s of millions of lines)
Proficiency in designing robust, flexible APIs and interfaces for profiling tools enabling seamless integration with various frameworks and custom code
Mastery of problem simplification: history of breaking down ill-defined problems in complex technical domains, designing effective solutions, and leading teams to implement them

Responsibilities

Architect and build scalable systems: drive design and implementation of AON profiling service's core systems, mastering IPC, memory management, and low-overhead architectures for multi-node, multi-process, multi-GPU, and cluster environments
Elevate software engineering excellence: promote high standards in software development, including design patterns, concurrency, parallelism, and advanced debugging for asynchronous systems, with commitment to code quality and robust testing
Lead, mentor, and innovate: guide and mentor engineers, provide impactful code reviews, shape technical roadmaps, proactively identify complex technical issues, break them down, and craft innovative solutions for ML workloads
Architect and build high-performance platforms: transform user needs into clear requirements and design documents, explore diverse approaches, make well-reasoned recommendations, and lead end-to-end feature development (planning, prototyping, implementation, testing, customer evaluation) across user applications, drivers, performance counter libraries, and lower-level platform/hardware abstraction layers
Collaborate across boundaries: partner effectively with diverse internal and external teams, leveraging exceptional communication and collaboration skills to integrate AON into the broader profiling and ML ecosystem

Skills

C++

IPC

Memory Management

Concurrency

Parallelism

Debugging

GPU Programming

Multi-GPU

Multi-Process

Multi-Node

Cluster Computing

Performance Profiling

Software Architecture

Code Review

Testing

Machine Learning

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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