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Electrical Engineer Nvidia Jobs in Atlanta, GA (NOW HIRING)

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Electrical Engineer Nvidia information

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$48.6K

$106.8K

$161.6K

How much do electrical engineer nvidia jobs pay per year?

As of Sep 6, 2026, the average yearly pay for electrical engineer nvidia in Atlanta, GA is $106,832.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,800.00 and $126,900.00 per year, depending on experience, location, and employer.

What is an electrical engineer Nvidia?

An Electrical Engineer at Nvidia is responsible for designing, developing, and testing hardware components for cutting-edge computing and AI technologies. They work on power distribution, high-speed circuit design, PCB layout, and system integration for GPUs, data centers, and autonomous systems. The role requires expertise in circuit design, signal integrity, and industry standards, often involving collaboration with cross-functional teams.

What are the key skills and qualifications needed to thrive as an electrical engineer Nvidia?

To thrive as an Electrical Engineer at Nvidia, you need a solid background in electrical engineering principles, digital and analog circuit design, and a relevant engineering degree. Proficiency with tools like Cadence, SPICE, and knowledge of hardware description languages, as well as familiarity with industry standards and certifications, is highly valued. Exceptional problem-solving skills, teamwork, and effective communication are key soft skills that set candidates apart. These competencies are critical because they ensure you can design innovative hardware, troubleshoot complex issues, and collaborate efficiently on cutting-edge technology projects.

What types of projects and technologies do electrical engineers at Nvidia typically work on?

Electrical Engineers at Nvidia are involved in designing, testing, and optimizing high-performance hardware systems, such as GPUs and AI accelerators, which support a wide range of cutting-edge applications. They work on board-level circuit design, power delivery, signal integrity, and system integration, often collaborating with cross-functional teams including hardware, software, and mechanical engineers. The fast-paced and innovative environment means engineers are continually exposed to new technologies and challenges, allowing for rapid professional growth and hands-on involvement in industry-leading products. This role offers the opportunity to directly influence Nvidia’s hardware platforms that shape advancements in gaming, artificial intelligence, and high-performance computing.

Can I work at NVIDIA as an electrical engineer?

Electrical engineers can work at NVIDIA in roles involving hardware design, circuit development, and system integration. The company often requires relevant experience, proficiency in tools like CAD and simulation software, and a bachelor's or master's degree in electrical engineering or a related field.

What are the most commonly searched types of Electrical Engineer Nvidia jobs in Atlanta, GA?

The most popular types of Electrical Engineer Nvidia jobs in Atlanta, GA are:

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For Electrical Engineer Nvidia jobs in Atlanta, GA, the most frequently searched job titles are:

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Electrical Engineer Nvidia jobs near you
Infographic showing various Electrical Engineer Nvidia job openings in Atlanta, GA as of August 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 85% In-person, and 15% Hybrid job distribution, with an average salary of $106,832 per year, or $51.4 per hour.

Senior Software Engineer, Simulation

AeroVect Technologies Inc.

Atlanta, GA • On-site

$120 - $160/hr

Other

Posted 27 days ago

Job description

Who We Are

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.

You will own and extend the simulation tooling. A significant part of the role is test quality. A test suite that produces flaky failures does not provide usable information. Determinism, reproducibility, and verifying that each gate is capable of failing are ongoing responsibilities rather than one-off tasks.

You Will

  • Build and extend the capabilities of the simulation environment: integration with the production autonomy stack, the interfaces it consumes, vehicle and actor models, and the range of environmental and operational conditions that can be represented

  • Maintain and improve that integration as the autonomy stack evolves, including fidelity work where the difference between simulated and real inputs changes how the stack behaves

  • Build and operate scenario execution in the cloud: orchestration, parallelism, result aggregation, artifact capture, and runtime cost modelling

  • Build and extend the evaluation layer that turns a run into a verdict — assertions and pass/fail criteria precise enough to gate a release and stable enough to avoid false failures

  • Build failure-triage tooling: failure clustering, per-failure recordings, and dashboards that autonomy engineers can use without assistance

  • Extend the scenario authoring tooling used by the V&V team, across backend and frontend

  • Maintain simulation foundations: determinism and reproducibility, pipeline performance, and extending coverage to additional maps and sites

You Have

  • Bachelor’s in Computer Science, Electrical Engineering, Robotics, or related field

  • Strong Python, with a track record of maintainable code in a shared codebase

  • Hands-on simulation experience for autonomous systems, familiarity with simulation platforms such as CARLA, Applied Intuition, Foretellix, NVIDIA Omniverse, IsaacSim, Gazebo, or a proprietary in-house simulatorWorking knowledge of simulation, modelling, and validation methodology, including how simulated results are used to support claims about real-world behaviour

  • Docker and Linux, distributed-systems fundamentals, and experience with GPU-based simulation environmentsCI/CD and cloud execution, experience integrating automated test workflows into CI for end-to-end validation coverage

  • Experience analyzing simulation output and telemetry to identify performance bottlenecks and failure modes

  • Debugging and profiling skills suited to distributed, GPU-bound systems

We Prefer

  • Master’s in Computer Science, Robotics, or related field

  • Experience designing and validating safety-critical systems in autonomous driving, aerospace, or robotics

  • Experience developing or maintaining autonomous vehicle software stacks (ROS/ROS2)

  • Cloud-based simulation infrastructure and large-scale distributed test execution

  • Sensor modelling (camera, lidar, radar), environment generation, or perception ground-truth pipelines

  • Automated testing, continuous integration, and data-driven validation

  • Log/bag re-simulation from recorded real-world data

  • Test-signal quality work: flake reduction, determinism debugging, golden-output comparison

  • Safety standards exposure: ISO 26262, ISO 21448 (SOTIF), UL4600, ISO 13849

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