Field Applications Engineer, Embedded Systems - NALA

Nvidia

Actively hiring
Santa Clara, CA Posted 61 days ago $108,000$178,250 / year

At a glance

AI generated

TL;DR

As a Field Applications Engineer at NVIDIA, you will support customers using the Jetson platform in embedded industrial applications, collaborating closely with sales teams to address customer technical needs. Your day-to-day involves deep engagement with clients to understand their system architectures and challenges, advising them on solutions leveraging Jetson SDK and edge AI inference software. You will also work alongside internal application and engineering teams to resolve issues, provide training to partners, and establish strong communication channels within the organization. Ideal candidates have a BS or MS in Electrical Engineering or Computer Science with 2+ years of experience in embedded design or technical customer support roles. Proficiency in Linux, C, C++, Python, and strong communication skills are essential, along with familiarity with NVIDIA GPU development, gStreamer, ROS, OpenCV, and AI technologies.

Skills

Linux C C++ Python NVIDIA GPU gStreamer ROS OpenCV Deep Learning AI Functional Safety

What you'll do

  • Work with customers to understand their system architectures and technical needs.
  • Help customers with Jetson SDK and edge AI inference software through direct support.
  • Collaborate with NVIDIA teams to ensure customer success in embedded systems development.
  • Reproduce issues and identify root causes to resolve customer challenges.
  • Provide technical and sales training to ecosystem and channel partners.

What we're looking for

  • BS or MS in Electrical Engineering or Computer Science or equivalent experience
  • 2+ years of work-related experience in embedded design or technical customer support
  • Expertise in Linux, embedded software, and application development
  • Proficiency in C, C++, and Python coding
  • Strong communication skills for collaboration with management and engineering
  • Experience with NVIDIA GPU development and tools like gStreamer, ROS, OpenCV
  • Knowledge of deep learning and AI technologies

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $167k
This role $143k
$97k most similar roles pay here $209k

This role pays less than 64% of similar roles. Most pay $137,000–$196,750 — the shaded band above. At the midpoint, this role pays about $143k versus about $167k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 824 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 812 roles with salary data.

Most-posted roles

View all roles at Nvidia

More like this

Similar roles

Field Applications Engineer

Broadcom

San Jose, CA 12 days ago $140,600$225,000
PCIe Python Kubernetes Docker AWS CI/CD PostgreSQL Git Jira Confluence Prometheus Grafana Ansible Terraform

Embedded Systems Software Engineer

Qualcomm

San Diego, CA 26 days ago $122,500$183,700
C Linux kernel gdb perf ftrace Ethernet VLANs TCP/IP QNX networking device drivers CPU utilization latency throughput networking virtualization upstream Linux kernel automotive SoCs embedded SoCs

Embedded Systems Engineer 4

Lam Research

Fremont, CA 11 days ago $119,000$261,000
C C++ Verilog VHDL SPI I2C PCIe EtherCAT LonWorks CANBus DeviceNet eMMC DDR Python PostgreSQL Mentorship Kubernetes AWS Terraform Docker CI/CD
Hybrid

Embedded Systems Engineer 3

Lam Research

Tualatin, OR 5 days ago
C C++ RTOS SPI I2C UART Altium Designer Cadence Allegro DX Designer Ethernet EtherCAT CAN Verilog VHDL Embedded Linux
Hybrid

Senior Field Applications Engineer

Motorola Solutions

Reston 5 days ago
Python Linux TCP/IP VLANs Spectrum Analyzers Network Analyzers Docker AWS Git CI/CD PostgreSQL Kubernetes Terraform RF theory RF spectrum monitoring Direction finding Geolocation technology RFeye ecosystem
Hybrid