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Nvidia Jetson Jobs (NOW HIRING)

Seyond

Software Engineer

Sunnyvale, CA · On-site

$100K - $200K/yr

Utilize edge AI platforms, such as NVIDIA Jetson, to deploy and test real-time perception software. * Develop and maintain software in Linux environments, ensuring high performance and reliability.

Seyond

Software Engineer

Sunnyvale, CA

$100K - $200K/yr

Utilize edge AI platforms, such as NVIDIA Jetson, to deploy and test real-time perception software. * Develop and maintain software in Linux environments, ensuring high performance and reliability.

Seyond

Software Engineer

Sunnyvale, CA · On-site

$100K - $200K/yr

Utilize edge AI platforms, such as NVIDIA Jetson, to deploy and test real-time perception software. * Develop and maintain software in Linux environments, ensuring high performance and reliability.

Swarmbotics AI

Software Deployment Engineer

Phoenix, AZ · On-site

The ideal candidate has deep expertise in Linux-based embedded systems, NVIDIA Jetson platforms, containerized deployments, and DevOps practices tailored for robotics systems operating in constrained ...

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Nvidia Jetson information

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How much do nvidia jetson jobs pay per hour?

As of Jun 11, 2026, the average hourly pay for nvidia jetson in the United States is $60.53, according to ZipRecruiter salary data. Most workers in this role earn between $50.72 and $69.47 per hour, depending on experience, location, and employer.

What is the difference between Nvidia Jetson vs Embedded Systems Engineer?

AspectNvidia JetsonEmbedded Systems Engineer
CredentialsKnowledge of AI, Linux, and hardware integrationDegree in Electrical, Computer Engineering, or related fields; certifications vary
Work EnvironmentHardware development, embedded AI applications, prototypingDesigning, developing, and testing embedded systems across industries
Industry UsageRobotics, AI, IoT, autonomous vehiclesConsumer electronics, automotive, aerospace, industrial automation

While Nvidia Jetson focuses on hardware platforms for AI and robotics, Embedded Systems Engineers design and develop the software and hardware for embedded devices across various industries. Both roles require knowledge of embedded systems, but Nvidia Jetson specialists are more hardware and AI-focused, whereas Embedded Systems Engineers have broader responsibilities in system design and integration.

What are the key skills and qualifications needed to thrive as an Nvidia Jetson Developer, and why are they important?

To excel as an Nvidia Jetson Developer, you need a strong background in embedded systems, computer vision, and programming languages such as Python and C++, often supported by a relevant engineering or computer science degree. Familiarity with the Jetson platform, CUDA programming, deep learning frameworks (like TensorFlow or PyTorch), and related SDKs is typically required. Problem-solving, creativity, and effective communication are essential soft skills for designing innovative AI solutions and collaborating across teams. These skills are crucial for developing efficient, real-time AI applications that leverage the full capabilities of Nvidia Jetson hardware.

What are Nvidia Jetson devices?

Nvidia Jetson refers to a series of small, powerful computers developed by Nvidia for edge AI, robotics, and embedded systems. These devices are designed to deliver high-performance computing and artificial intelligence capabilities in a compact form factor. Jetson modules, such as the Jetson Nano, TX2, Xavier NX, and AGX Xavier, are widely used in applications like robotics, drones, smart cameras, and industrial IoT solutions. They provide developers with GPU-accelerated parallel processing, making them suitable for deep learning, computer vision, and other AI workloads at the edge. Jetson devices also come with a comprehensive software stack, including support for the Nvidia JetPack SDK.

What are some common challenges faced by engineers working with Nvidia Jetson platforms, and how can they be addressed?

Engineers working with Nvidia Jetson platforms often encounter challenges such as optimizing deep learning models for edge deployment, managing power and thermal constraints, and integrating various sensors and peripherals. Addressing these challenges typically involves utilizing Nvidia's development tools like JetPack SDK, TensorRT for model optimization, and carefully profiling system performance. Collaborating closely with software and hardware teams, staying updated with Nvidia's documentation, and participating in relevant developer forums can also help in solving technical hurdles effectively.
Infographic showing various Nvidia Jetson job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 75% In-person, and 25% Remote job distribution, with an average salary of $125,908 per year, or $60.5 per hour.

Forward Deployed Engineer (FDE) - United States

Maneva

Chicago, IL • On-site

Full-time

Posted 14 days ago

Job description

Maneva is a leader in AI-powered computer vision and predictive systems for manufacturers, delivering integrated solutions that connect edge devices and factory systems with cloud software to optimize production quality and throughput. As a Forward Deployed Engineer, you will play a pivotal role in deploying advanced AI systems directly into customer environments, acting as the primary technical contact and trusted advisor for strategic manufacturing accounts.
Key responsibilities include:
  • Own the end-to-end lifecycle of AI deployment for manufacturing clients, from scoping and integration to production hardening and handover.
  • Embed with customer operations and IT teams, serving as the main technical advisor and point of contact.
  • Integrate AI vision systems with OT/IT/cloud stacks, including OPC-UA/Modbus/PLCs, NVIDIA Jetson edge inference, ERP, and customer cloud platforms.
  • Build and iterate data pipelines and customer-side data flywheels, covering edge-to-cloud capture, model deployment, monitoring, and feedback loops.
  • Troubleshoot software, networking, and integration issues in live production environments.
  • Document architectures and configurations, producing formal handover artifacts for long-term support.
  • Train customer operators and engineers in both French and English to ensure successful adoption and operation of deployed systems.
  • Participate in pre-sales scoping calls and contribute field learnings to the product and engineering roadmap, helping shape reusable deployment patterns and internal tooling.
  • Support on-site data collection and annotation as needed.

Requirements
Required Qualifications:
  • 6+ years of experience combining production software engineering with industrial automation and/or applied AI
  • Proven experience shipping and supporting production software systems deployed into customer infrastructure
  • Production Python development experience with hands-on use of Linux, Docker, and Git in production environments
  • Cloud deployment and operations experience with at least one major platform (AWS, Azure, or GCP)
  • Hands-on experience with at least one of: OPC-UA/Modbus/PLC integration, NVIDIA Jetson (or equivalent) edge platforms, or GenICam/industrial vision systems
  • Networking fundamentals for industrial deployments, including TCP/IP, VLANs, and firewalls
  • Experience in a customer-facing engineering role as the primary technical contact for external stakeholders
  • Professional working proficiency in English
Preferred Qualifications:
  • Professional experience working in industrial automation or manufacturing environments involving OT/IT integration

Benefits
Why Join Us?
  • Be part of a fast-growing team creating transformative solutions for manufacturing.
  • Work on cutting-edge AI and MLOps tools with real-world impact.
  • Enjoy a collaborative and supportive work environment.
  • Opportunities for professional growth and career advancement.

Apply