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Cuda Kernel Engineer Jobs in Boston, MA (NOW HIRING)

ICONSTAFF

Machine Learning Engineer

Cambridge, MA · On-site +1

Machine Learning Engineer - Computer Vision & Robotics Tycho.AI is redefining the future of ... CUDA kernel development and model optimization (quantization, pruning, distillation). * Experience ...

Motional

Machine Learning Systems Engineer

Boston, MA · On-site +1

Kernel Development : Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads. * Data Pipeline Engineering : Optimize robust data loading pipelines that ...

Zoox

Software Engineer - C++ GPU Performance

Boston, MA

$168K - $239K/yr

Experience with GPU kernel development in a real-time environment, including PTX-level programming, CPU SIMD instructions (e.g., AVX intrinsics), and custom CUDA layers with frameworks like TensorRT ...

Zoox

Software Engineer - C++ GPU Performance

Boston, MA · On-site

$168K - $239K/yr

Experience with GPU kernel development in a real-time environment, including PTX-level programming, CPU SIMD instructions (e.g., AVX intrinsics), and custom CUDA layers with frameworks like TensorRT ...

Zoox

Software Engineer - C++ GPU Performance

Boston, MA

$168K - $239K/yr

Experience with GPU kernel development in a real-time environment, including PTX-level programming, CPU SIMD instructions (e.g., AVX intrinsics), and custom CUDA layers with frameworks like TensorRT ...

Motional

Machine Learning Systems Engineer

Boston, MA · On-site +1

$144K - $192K/yr

Kernel Development : Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads. * Data Pipeline Engineering : Optimize robust data loading pipelines that ...

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Cuda Kernel Engineer information

What are common challenges faced by CUDA Kernel Engineers when optimizing GPU code for performance?

Cuda Kernel Engineers often encounter challenges such as managing memory hierarchy efficiently, minimizing data transfer between host and device, and avoiding thread divergence. Ensuring optimal occupancy and maximizing parallelism while preventing bottlenecks like bank conflicts or uncoalesced memory access are also key concerns. Collaborating closely with software architects and data scientists is common, as solutions frequently require balancing algorithmic accuracy with hardware limitations. Addressing these challenges requires continuous profiling, testing, and iterative optimization.

What is a CUDA Kernel Engineer?

Cuda Kernel Engineers are specialized software developers who design, implement, and optimize parallel computing algorithms using NVIDIA's CUDA platform. They write 'kernels,' which are functions that run on Graphics Processing Units (GPUs) to accelerate computational tasks in areas such as machine learning, scientific simulations, and graphics rendering. These engineers need strong skills in C/C++ programming, GPU architecture, and performance optimization techniques. Their work is crucial for applications that require high-speed data processing and efficient resource utilization.

What skills and qualifications are needed to be a CUDA Kernel Engineer?

To thrive as a CUDA Kernel Engineer, you need strong proficiency in C/C++ programming, parallel computing concepts, and a solid foundation in GPU architectures, typically supported by a degree in computer science or a related field. Expertise in NVIDIA CUDA toolkits, GPU profiling tools like Nsight, and familiarity with version control systems are essential. Analytical thinking, problem-solving abilities, and effective collaboration skills help engineers optimize code and work well within development teams. These skills and qualities are crucial for delivering high-performance, scalable GPU solutions in computationally intensive applications.
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Cuda Kernel Engineer jobs near you
Infographic showing various Cuda Kernel 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.

Machine Learning Engineer

ICONSTAFF

Cambridge, MA • On-site, Remote

Full-time

Medical, Retirement

Re-posted 8 days ago

Job description

Machine Learning Engineer – Computer Vision & Robotics


Tycho.AI is redefining the future of autonomous intelligence. Spun out of MIT and backed by DoD contracts, we are building breakthrough AI and autonomy solutions for unmanned systems operating in GPS-denied and contested environments. We are a fast-growing, dual-use technology company at the forefront of national security and commercial innovation, with a mission to push the boundaries of what autonomous systems can achieve.

Joining Tycho.AI means being part of a team shaping the next decade of autonomy from defense applications to commercial opportunities in areas like logistics, disaster response, and beyond. If you want to work at the cutting edge of AI/ML and robotics with a company that’s poised for major impact and growth, we want to hear from you.


Responsibilities

  • Design, develop, and optimize ML models for computer vision and robotics tasks.
  • Build robust training and fine-tuning pipelines for large-scale datasets.
  • Integrate ML systems into real-world platforms, bridging research and production.
  • Write clean, efficient, and maintainable code across Python and/or C++.
  • Stay current on research and apply state-of-the-art techniques in autonomy and perception.


Requirements

  • Bachelor’s or advanced degree in Computer Science, Engineering, or related field.
  • Hands-on experience applying ML to computer vision and/or robotics.
  • Proficiency with PyTorch or TensorFlow.
  • Strong coding skills in Python or C++ (ideally both).
  • Experience deploying ML models and building training pipelines.
  • Familiarity with Git and collaborative software development practices.


Nice to Have:

  • CUDA kernel development and model optimization (quantization, pruning, distillation).
  • Experience with ONNX, TensorRT, or OpenVINO for deployment.
  • Robotics middleware (ROS2).
  • SLAM, 3D perception, or sensor fusion (LiDAR, IMU).
  • Real-time or low-latency inference pipelines.


Why Tycho.AI

  • Be part of a rapidly scaling startup defining the future of autonomous intelligence.
  • Collaborate with top engineers and researchers from MIT, Google, and across the defense innovation ecosystem.
  • Direct impact on national security missions and dual-use commercial applications.
  • Along with a competitive salary and options, Tycho.AI offer a robust benefits package, including many options from medical insurance with 80% company contribution to pet insurance and a 401(k) retirement plan.