Field Applications Engineer, Embedded Systems - NALA at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, ElectronicsIndustries

Requirements

BS or MS in Electrical Engineering or Computer Science or equivalent experience
8+ years of work-related experience in a high-tech electronics industry in an embedded design role or technical customer support role
Linux, embedded SW and embedded application expertise
C, C++, and Python coding
Capable of working in a rapidly changing environment without losing focus
Strong analytical and problem-solving skills
Strong written and oral communications skills in English with the ability to effectively collaborate with management and engineering

Responsibilities

Engage customers and develop a keen understanding of their system architectures, challenges, objectives, and technical needs – and help to define highly valued solutions that meet these needs
Be the trusted advisor for our customers, help them with our Jetson SDK and edge AI inference supporting our sales partners and customers
Work closely with the NVIDIA applications and engineering team to ensure customers are successful in developing their embedded systems, answer their questions directly, via email, and on the NVIDIA developer forum
Provide technical and sales training to ecosystem and channel partners
Establish trusted relationships and communication channels with internal teams

Skills

Key technologies and capabilities for this role

Embedded SystemsEmbedded SoftwareLinuxCC++JetsonJetson SDKEdge AI InferenceGPU AI

Questions & Answers

Common questions about this position

What is the base salary range for this Field Applications Engineer role?

The base salary range is 160,000 USD - 253,000 USD, determined based on location, experience, and pay of employees in similar positions.

What benefits are offered for this position?

You will be eligible for equity and benefits.

Is this role remote or does it require travel or office presence?

This information is not specified in the job description.

What are the key required skills for this position?

Required skills include BS or MS in Electrical Engineering or Computer Science, 8+ years of experience in embedded design or technical customer support, Linux and embedded SW expertise, C, C++, and Python coding, strong analytical and problem-solving skills, and excellent communication skills.

What experience will help me stand out as a candidate?

NVIDIA GPU development experience, experience with gStreamer, ROS and/or OpenCV, and Deep Learning and/or AI experience will help you stand out.

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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