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Remote Cuda Developer Jobs in Amesbury, MA (NOW HIRING)

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Remote Cuda Developer information

See Amesbury, MA salary details

$90.2K

$110.7K

$146.3K

How much do remote cuda developer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for remote cuda developer in Amesbury, MA is $110,675.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $124,200.00 per year, depending on experience, location, and employer.

What is a remote CUDA developer?

A Remote CUDA Developer is a software engineer who specializes in using NVIDIA's CUDA (Compute Unified Device Architecture) platform to develop parallel computing applications, often for high-performance tasks like machine learning, scientific computing, or data analysis. They work remotely, collaborating with teams online rather than being physically present in an office. These developers write and optimize code to run efficiently on NVIDIA GPUs, enabling applications to process large amounts of data much faster than traditional CPU-only solutions.

What skills and qualifications are needed to thrive as a remote CUDA developer?

To thrive as a Remote CUDA Developer, you need strong proficiency in C/C++ programming, parallel computing concepts, and a solid understanding of GPU architecture, typically backed by a degree in computer science or a related field. Experience with NVIDIA CUDA toolkit, GPU debugging tools, and version control systems like Git is commonly required. Excellent problem-solving skills, self-motivation, and effective remote communication abilities help distinguish high performers in this role. These skills are vital for efficiently delivering high-performance computing solutions and collaborating seamlessly with distributed teams.

How does a remote CUDA developer typically collaborate with team members across different locations?

As a Remote CUDA Developer, you will frequently collaborate with cross-functional teams such as data scientists, software engineers, and product managers through virtual meetings, code reviews, and collaborative platforms like GitHub or GitLab. Clear communication and thorough documentation are essential since team members may be in different time zones. You can expect to participate in regular stand-ups, sprint planning, and peer programming sessions, ensuring alignment and smooth integration of your GPU-accelerated code into larger projects. Tools like Slack, Zoom, and project management platforms help maintain connectivity and workflow efficiency.

What is the difference between Remote Cuda Developer vs Remote Machine Learning Engineer?

AspectRemote Cuda DeveloperRemote Machine Learning Engineer
Required CredentialsCUDA programming certifications, computer science degreeMachine learning certifications, data science background
Work EnvironmentSoftware development, GPU optimizationModel development, data analysis
Industry UsageHigh-performance computing, gaming, AIAI, data science, predictive modeling

Remote Cuda Developers focus on GPU programming and optimization using CUDA, primarily in high-performance computing and AI applications. Remote Machine Learning Engineers develop and deploy machine learning models, often utilizing GPU resources but with a broader focus on data and algorithms. While both roles may involve GPU expertise, Cuda Developers specialize in low-level programming, whereas Machine Learning Engineers work on model development and deployment.

What cities near Amesbury, MA are hiring for Remote Cuda Developer jobs?

Cities near Amesbury, MA with the most Remote Cuda Developer job openings:

Remote Cuda Developer jobs near you
Infographic showing various Remote Cuda Developer job openings in Amesbury, MA as of August 2026, with employment types broken down into 77% Full Time, 10% Part Time, and 13% Contract. Highlights an 100% Remote job distribution, with an average salary of $110,675 per year, or $53.2 per hour.

Software Engineer, Embedded Systems

MatrixSpace

Burlington, MA • Remote

$150K - $185K/yr

Full-time

Re-posted 15 days ago

Job description

Help bring AI and machine learning capabilities to embedded edge platforms by building high-performance software that runs close to the hardware.

MatrixSpace develops AI-enabled radar and sensing systems that help people understand what's happening in the world around them. By combining advanced radar, edge computing, and AI, we deliver situational awareness in environments where traditional sensing solutions struggle.

We're looking for a hands-on Embedded Software Engineer to build high-performance software that runs close to the hardware. You'll develop production embedded applications in C/C++, optimize software for resource-constrained edge platforms, and work across Linux, networking, and system-level software.

If you're the kind of engineer who can read complex C/C++ code like a book, enjoys understanding entire systems rather than isolated components, and loves solving practical engineering problems, we'd love to talk.

What You'll Do

  • Port, optimize, and enhance platform software for embedded and resource-constrained compute environments.
  • Deploy, validate, profile, and optimize AI/ML-enabled applications on edge hardware.
  • Develop production-quality software using C/C++, Python, Golang, and Linux-based technologies.
  • Collaborate with Data Science teams to integrate AI/ML models into production software pipelines.
  • Work across Linux kernel, device interfaces, networking, and system-level software components.
  • Participate in architecture reviews, code reviews, testing, troubleshooting, and technical planning.

What We're Looking For

This position requires working directly or indirectly with the US Government in restricted environments. Candidates must be legally authorized to work in the United States without employer sponsorship and may be required to obtain and maintain a U.S. government security clearance in the future.

THIS IS NOT A FULLY REMOTE POSITION.

Required

  • Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, Robotics, or a related technical field, or equivalent practical experience.
  • 4+ years of professional software engineering experience or equivalent demonstrated expertise
  • Professional experience building, deploying, and maintaining production embedded software systems on edge devices with constrained CPU, GPU, memory, storage, and power resources.
  • Expert-level proficiency in C/C++ with the ability to quickly understand, debug, and extend large existing codebases. This role is not a fit for candidates without deep C/C++ experience. Working knowledge of Golang and Python3.8+ preferred.
  • Strong experience with Yocto-based embedded Linux distributions, including image customization, package management, board support packages, kernel configuration and tuning, and production deployment workflows.
  • Strong debugging, profiling, and performance optimization skills on constrained compute platforms.
  • Ability to collaborate effectively across software, firmware, DevOps, data science, and hardware teams.

Someone Who Will Thrive in This Role

  • Enjoys understanding complete systems—not just individual components.
  • Takes ownership of complex technical problems and follows them through to production.
  • Is comfortable diving into large existing codebases and becoming productive quickly.
  • Values practical, reliable engineering over unnecessary complexity.
  • Collaborates effectively across software, firmware, hardware, and AI teams.
  • Has experience at smaller or fast-growing companies where engineers own broad portions of the product rather than a single isolated component.
  • Has experience developing connected devices, IoT platforms, fleet management systems, robotics, or other distributed edge computing products.

Bonus Points

  • Experience deploying AI/ML models usingTensorRT, ONNX Runtime,PyTorch, TensorFlow Lite, or similar frameworks.
  • Experience with NVIDIA Jetson, CUDA, GPUs, NPUs, or other edge accelerators.
  • Background in radar, RF sensing, robotics, autonomy, perception systems, signal processing, or sensor fusion.
  • Experience with hardware-in-the-loop testing, board bring-up, and embedded platform validation.

At MatrixSpace, software engineering is where advanced sensing technology meets real-world deployment. You'll help bring AI-powered capabilities to edge platforms so our customers can gain actionable insights from complex environments. If that sounds exciting, we'd love to hear from you.