[Remote] Senior Manager, Abstraction Layer Engineering – Autonomous Platform at NVIDIA

California, United States

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Not SpecifiedCompensation

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

Full TimeJob Type

UnknownVisa

Autonomous Vehicles, AI, RoboticsIndustries

Requirements

MS or higher in computer engineering, computer science or related engineering fields (or equivalent experience)
12+ overall years of relevant industry experience and 8+ years of managing a team
Excellent C and C++ programming skills
Experience developing and debugging multithreaded/distributed applications like multimedia systems, game engines, etc
Strong knowledge of programming and debugging techniques, especially for parallel and distributed architectures
Strong knowledge on Linux, Android, and/or other real-time operating systems
Experience with frameworks for robotics such as ROS and/or for multimedia such as GStreamer
Thrive on writing low latency, highly performant code
Phenomenal communication and analytical skills
Self-motivated and a great teammate
Ways to stand out
Understanding of embedded architectures and developing software in heterogeneous architectures, including GPUs
Knowledge of automotive systems, notably ADAS applications, AUTOSAR and drive by wire systems
Software development for modern OpenGL (Core Profile) and Linux
Experience with version control systems GIT and build system like CMake/Bazel
Be hands-on and work well within a team of algorithm, software and hardware engineers, with a significant level of detail orientation and a penchant for data organization and presentation

Responsibilities

Lead the VAL and SAL teams, designing and developing optimal software abstractions and plugin frameworks to interface with real-world vehicle and sensor systems, consistently exceeding customer expectations
Build efficient and user-friendly mechanisms to improve software integration across a wide range of vehicles and sensor configurations
Work on core areas such as component abstraction layers, sensor and actuator interfacing, and inter-process data sharing and communication, enabling reliable and scalable autonomous driving solutions
Solidify existing frameworks and software components, validating improvements through extensive real-world and synthetic testing to enhance computational performance and system utilization
Perform in-vehicle tests, collect and analyze sensor and vehicle data, and support the completion of autonomous drive missions
Develop unit tests and documentation for key features, evaluate software quality, and propose corrective actions in alignment with industry best practices
Develop highly efficient, production-quality C++ code, demonstrating parallel computing capabilities through GPGPU (CUDA) to accelerate processing workloads
Follow industry safety and quality standards, including MISRA and other automotive-grade software development practices

Skills

Key technologies and capabilities for this role

C++software architectureabstraction layerssensor interfacingactuator interfacingplugin frameworksinter-process communicationunit testingreal-world testingautonomous drivingrobotics

Questions & Answers

Common questions about this position

What education and experience are required for this role?

Candidates need an MS or higher in computer engineering, computer science, or related fields (or equivalent experience), 12+ years of relevant industry experience, and 8+ years of managing a team.

What key technical skills are needed for this position?

Excellent C and C++ programming skills are required, along with experience developing and debugging multithreaded/distributed applications, strong knowledge of Linux/Android/real-time OS, and familiarity with ROS or GStreamer frameworks.

What is the salary or compensation for this role?

This information is not specified in the job description.

Is this position remote or does it require office work?

This information is not specified in the job description.

What soft skills or qualities make a strong candidate?

Phenomenal communication and analytical skills, being self-motivated, and a great team player are essential, along with thriving on writing low latency, highly performant code.

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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