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Neural Dsp Jobs (NOW HIRING)

Ambarella

Develop a deep understanding of Ambarella's DSP architecture to ensure the efficient use of ... Familiarity with Neural Network frameworks such as TensorFlow, caffe, pytorch etc. * Excellent ...

quadric, Inc

Senior Performance Architect

Burlingame, CA

$188K/yr

... neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control ...

quadric, Inc

Senior Performance Architect

Burlingame, CA · On-site

$188K/yr

... neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control ...

quadric, Inc

AI Applications Engineer

Burlingame, CA · On-site

$110K - $270K/yr

... neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control ...

quadric, Inc

AI Applications Engineer

Burlingame, CA

$110K - $270K/yr

... neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control ...

quadric, Inc

AI Applications Engineer

Burlingame, CA · On-site

$110K - $270K/yr

... neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control ...

quadric, Inc

AI Kernel Engineer

Burlingame, CA · On-site

$110K - $270K/yr

... neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control ...

quadric, Inc

AI Kernel Engineer

Burlingame, CA · On-site

$110K - $270K/yr

... neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control ...

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How much do neural dsp jobs pay per hour?

As of Jul 22, 2026, the average hourly pay for neural dsp in the United States is $16.28, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $17.55 per hour, depending on experience, location, and employer.

What are the common daily tasks and team interactions for a Neural DSP Engineer?

A Neural DSP Engineer typically spends their days designing, implementing, and optimizing algorithms that combine neural network models with digital signal processing techniques. This can involve coding, running simulations, evaluating system performance, and troubleshooting both software and, in some cases, embedded hardware. Collaboration is frequent, as you will often work closely with software engineers, data scientists, audio engineers, or product managers to ensure that neural DSP solutions meet project requirements. Regular meetings and code reviews are standard, and you may participate in cross-functional teams working on research, prototyping, or product development. This collaborative environment fosters both technical growth and the exchange of new ideas.

What is a Neural DSP job?

A Neural DSP job typically involves working with digital signal processing (DSP) for audio applications, particularly in developing software and hardware for music production and guitar effects. Employees in these roles may focus on algorithm development, software engineering, machine learning, or sound design. The job often requires expertise in audio signal processing, programming languages like C++ or Python, and an understanding of music technology.

What are the key skills and qualifications needed to thrive in the Neural Dsp position, and why are they important?

To thrive as a Neural DSP (Digital Signal Processing) Engineer, you need a strong background in digital signal processing, neural network design, and proficiency with programming languages such as C++, Python, or MATLAB, typically backed by a degree in electrical engineering, computer science, or a related field. Experience with DSP development tools, neural network frameworks (like TensorFlow or PyTorch), and possibly embedded systems or audio processing platforms is highly valued. Excellent problem-solving abilities, adaptability, and effective collaboration are key soft skills in this multidisciplinary role. These abilities ensure you can design innovative neural DSP solutions, integrate them effectively into products, and work seamlessly across teams to meet cutting-edge technology needs.

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Neural Dsp jobs near you
Infographic showing various Neural Dsp job openings in the United States as of July 2026, with employment types broken down into 90% Full Time, and 10% Contract. Highlights an 90% In-person, and 10% Remote job distribution, with an average salary of $33,871 per year, or $16.3 per hour.
Software Engineer II: AI Compiler Engineer

Software Engineer II: AI Compiler Engineer

Cadence Design Systems, Inc.

Austin, TX • On-site

$96K - $132K/yr

Full-time

Posted 6 days ago

Job description

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.
Job Description
Cadence Design Systems Inc. is looking for a motivated Software Engineer II: AI Compiler Engineer to work with us.
As a Software Engineer II: AI Compiler Engineer you will work with complex high performance SoC's, and is one of the best kept secrets within the semi IP world powering AR/VR, HiFi Audio and Speech, Vision, Imaging and hundreds of intelligent IoT applications.
Be a part of a team that develops an AI graph compiler that takes as input Neural Networks (NNs) created in frameworks such as PyTorch or TensorFlow and converts them into optimized code suitable for execution on special-purpose and embedded platforms.
Cadence is also a Fortune 100 Best Companies to Work For.
Job Description:
  • Developing a deep learning compiler stack that takes neural network descriptions (CNNs/RNNs) created in frameworks such as Caffe, PyTorch, TensorFlow, etc. and converts them into code suitable for execution on special-purpose and embedded platforms.
  • Use modern compiler frameworks such as LLVM and MLIR.
  • Developing optimized implementations of a variety of neural-network operations and integrating them into a runtime framework
  • Developing new optimization techniques and algorithms to efficiently map CNNs onto a wide range of Xtensa processors and specialized hardware.
  • Benchmarking end-to-end network performance on a variety of DSP and special-purpose accelerator platforms.
  • Enhancing the framework to improve overall functionality and performance on the various hardware platforms.
  • Devising multiprocessor/multicore partitioning and scheduling strategies.
  • Developing complex programs to validate the functionality and performance of the CNN application programming kit.
  • Working with hardware designers to identify opportunities for additional hardware acceleration of neural network functions.
  • Working with industry-leading partners and customers to design and standardize neural network APIs..

Requirements:
  • Complete Bachelor in Computer Science or Computer Engineering or equivalent experience.
  • A high level of C and C++ programming expertise with 3-5+ years of experience is required.
  • Expertise in software development on Linux and Windows systems including test, debug and release is required.
  • Knowledge of and experience with a state-of-the-art compiler stack such as LLVM and MLIR.
  • Experience implementing compilation techniques such loop optimization, polyhedral models, and IR construction/transition/lowering techniques.

Nice to have:
  • Master or PhD.
  • 3+ years of experience working on a production compiler is highly desired.
  • Python experience highly desired
  • Prior work with CNNs and familiarity with deep learning frameworks (TensorFlow, Caffe/2, etc.) is a strong plus
  • Experience programming and optimizing for embedded platforms such as DSPs with DMA engines highly desired
  • Familiarity with the state-of-the-art deep learning compilation approaches (Glow, TVM, XLA, etc.) is a plus
  • Familiarity with various deep learning networks and their applications (Classification/Segmentation/Object Detection/RNNs) is a plus
  • Knowledge of neural net exchange formats (ONNX, NNEF) is a plus

Additional Job Details:
  • Employment term: 40 hours/week.
  • Hybrid work.
  • Competitive benefits.

Cadence is the only company that provides the expertise and tools, IP, and hardware required for the entire electronics design chain, from chip design to chip packaging to boards and to systems. We enable electronic systems and semiconductor companies to create innovative products that transform the way people live, work, and play. Our products are used in mobile, consumer, cloud datacenter, automotive, aerospace, IoT, industrial and other market segments.
For more information, access http://www.cadence.com
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