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Cuda Engineer Jobs in Boston, MA (NOW HIRING)

Motional

Perception Engineer

Boston, MA · Remote

Perception Engineer. Ref. No. N322 BOSTON - REMOTE U.S. ONLY FULL-TIME What You'll Do: * Connect ... TensorRT/CUDA, * CI/CD pipelines, and * Git. Ref Job No. N322

New

Motional

Staff Engineer

Boston, MA

$205K - $272K/yr

Strong programming skills in C++ and/or CUDA programming The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills ...

Motional

Staff Engineer

Boston, MA · On-site +1

$205K - $272K/yr

Strong programming skills in C++ and/or CUDA programming The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills ...

ASUS

Senior Computer Vision Engineer

Boston, MA · On-site

$164K - $237K/yr

Familiarity with GPU/CUDA programming for accelerated vision processing is a plus. * Flexibility to attend virtual meetings with the Taiwan-based team at least three nights per week. * Excellent ...

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All JobsCuda Engineer JobsCuda Engineer Jobs in Boston, MA

Cuda Engineer information

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$39.7K

$116.5K

$149.4K

How much do cuda engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for cuda engineer in Boston, MA is $116,545.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,100.00 and $147,700.00 per year, depending on experience, location, and employer.

What is a CUDA engineer?

CUDA Engineers are software developers who specialize in using NVIDIA's CUDA (Compute Unified Device Architecture) platform to write programs that run on Graphics Processing Units (GPUs). They optimize and accelerate computational tasks by parallelizing code, making use of GPUs’ capabilities for high-performance computing. CUDA Engineers often work in fields like machine learning, scientific computing, and graphics, where large amounts of data need to be processed quickly. Their expertise includes proficiency in C/C++, CUDA programming, and understanding GPU hardware and parallel computing concepts.

What is the difference between Cuda Engineer vs GPU Developer?

AspectCuda EngineerGPU Developer
Required CredentialsBachelor's or Master's in Computer Science, Engineering, or related; knowledge of CUDA, C++, parallel programmingBachelor's or Master's in Computer Science, Engineering, or related; experience with GPU programming, CUDA, OpenCL
Work EnvironmentResearch labs, tech companies, hardware firms focusing on GPU accelerationSoftware development teams, gaming, AI, scientific computing sectors
Employer & Industry UsageHardware manufacturers, AI companies, high-performance computing firmsGame development, scientific research, machine learning applications

While both roles involve GPU programming and CUDA expertise, a Cuda Engineer primarily focuses on developing and optimizing CUDA-based solutions for hardware acceleration. In contrast, a GPU Developer works on broader GPU programming tasks, including application development across various platforms. The roles often overlap but differ in scope and specific focus areas.

How much do Cuda engineers make?

Cuda engineers typically earn between $80,000 and $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in GPU programming and parallel computing tend to have higher salaries. Certifications and a strong understanding of CUDA tools can also influence compensation.

What are some common challenges faced by CUDA engineers when optimizing GPU-accelerated applications?

CUDA Engineers frequently encounter challenges such as managing memory effectively between the host and the device, optimizing kernel performance, and minimizing data transfer bottlenecks. Debugging parallel code can also be complex due to race conditions and the difficulty of reproducing timing-related bugs. Collaborating closely with software developers and data scientists is essential to ensure that GPU resources are leveraged efficiently and that the application's overall performance meets project goals.

What are the key skills and qualifications needed to thrive as a CUDA engineer?

To thrive as a CUDA Engineer, you need a strong proficiency in C/C++ programming, parallel computing concepts, and deep knowledge of GPU architectures, often supported by a computer science or engineering degree. Experience with NVIDIA CUDA Toolkit, profiling/debugging tools, and sometimes certifications like NVIDIA DLI are highly valuable. Strong problem-solving, attention to detail, and effective communication skills help you optimize code and collaborate across teams. These skills ensure efficient development of high-performance GPU applications and successful project delivery in compute-intensive fields.

Are CUDA engineers in demand?

CUDA engineers are in high demand due to the increasing use of GPU computing in fields like artificial intelligence, machine learning, and high-performance computing. Skills in CUDA programming, parallel processing, and related tools are highly valued by employers across technology, research, and industry sectors.
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Cuda Engineer jobs near you
Infographic showing various Cuda Engineer job openings in Boston, MA as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $116,545 per year, or $56 per hour.

Principal Engineer, Team Lead - Behaviors

Motional

Boston, MA • On-site

Other

Re-posted 29 days ago

Job description

On our Behaviors team (Prediction and ML Planner), you will have the opportunity to work with world-class ML engineers, whose mission is to make self-driving vehicles a reality and to create a positive social impact. The Behaviors team develops ML models that learn how different agents navigate complex real-world traffic scenarios. We leverage these models to set the behavior of our self-driving vehicle, and predict the behavior of other agents such as vehicles and vulnerable road users. 

We are looking for proven leaders and technical experts who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and interested in pursuing career growth with a fast-growing company.

What You'll Be Doing:
  • Define and execute motion planning and prediction projects that improve our self-driving vehicles' capability to safely, comfortably and legally navigate complex traffic scenarios
  • Lead, manage and grow a team of engineers
  • Design and lead the implementation of behavior models that leverage the latest advancements in machine learning, generative AI and reinforcement learning
  • Productionize and deploy solutions onto autonomous vehicle fleets
  • Collaborate with perception, simulation, data platform and integration teams to validate and enhance your products' on-road performance
  • Communicate strategies, progress and challenges to executive leadership
What We're Looking for:
  • Masters or Ph.D. in Computer Science or a related technical field; or equivalent industry experience
  • Proven leadership skills at executing large, complex technical initiatives
  • Extensive experience managing and leading engineers
  • Experience with deep learning frameworks such as TensorFlow or PyTorch
  • Fluency in Python, including standard scientific computing libraries
  • Proven track record of designing, developing and deploying ML solutions for autonomous vehicles or robotics
  • Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods 
  • Excellent communication and interpersonal skills
Bonus Points:
  • Experience with embedded systems and real-time optimization, especially in the autonomous driving industry
  • Experience with state of the art generative AI, and/or reinforcement learning, paradigms
  • Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.)
  • Strong programming skills in C++ and/or CUDA programming

Apply