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Machine Learning Hardware Jobs (NOW HIRING)

Qualcomm

Machine Learning Engineer

San Diego, CA · On-site

... hardware (co-designed with machine learning software) for inference or training solutions. • Assists in the development of optimized software to enable AI models deployed on hardware (e.g., machine ...

Qualcomm

Machine Learning Engineer

San Diego, CA · On-site

$122.80K - $184.20K/yr

Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software. Minimum Qualifications: • ...

IMC

Hardware Machine Learning Engineer

Chicago, IL

$127.20K - $167.90K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it from the ground up. This is an initiative where you'll have the rare opportunity to architect ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it from the ground up. This is an initiative where you'll have the rare opportunity to architect ...

Brahma Consulting Group

Head of Hardware

Palo Alto, CA

$145.20K - $191.60K/yr

We are seeking an experienced Head of Hardware to lead our hardware engineering efforts at an innovative AI startup revolutionizing chip design through machine learning. This pivotal leadership role ...

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How much do machine learning hardware jobs pay per hour?

As of May 31, 2026, the average hourly pay for machine learning hardware in the United States is $24.59, according to ZipRecruiter salary data. Most workers in this role earn between $17.55 and $27.88 per hour, depending on experience, location, and employer.

What is a Machine Learning Hardware job?

A Machine Learning Hardware job involves designing, optimizing, and developing specialized hardware to accelerate machine learning workloads. Professionals in this field work on hardware architectures like GPUs, TPUs, FPGAs, and custom accelerators to improve efficiency, performance, and power consumption. They collaborate with software engineers and data scientists to optimize hardware-software co-design. This role requires expertise in computer architecture, parallel computing, and low-level programming.

What are the key skills and qualifications needed to thrive in the Machine Learning Hardware position, and why are they important?

To thrive in Machine Learning Hardware, you need a solid background in computer engineering, digital design, and machine learning principles, often supported by a degree in electrical engineering, computer engineering, or a related field. Familiarity with hardware description languages (such as VHDL or Verilog), simulation tools, FPGA/ASIC development platforms, and possibly certifications in hardware design or ML accelerators is valuable. Collaboration, problem-solving, and the ability to communicate complex technical ideas effectively are essential soft skills. These skills enable you to design and optimize specialized hardware solutions that accelerate machine learning workloads and foster interdepartmental innovation.

What are the typical day-to-day responsibilities for a Machine Learning Hardware engineer?

As a Machine Learning Hardware engineer, your daily tasks often include collaborating with data scientists and software engineers to understand computational requirements, designing and prototyping hardware accelerators, and optimizing existing architectures for improved performance and efficiency. You might work with simulation tools to model new designs, validate hardware functionality, and troubleshoot issues during integration. The role typically involves both independent technical work and teamwork across hardware and AI/ML departments. This position requires keeping up to date with emerging technologies to ensure your solutions remain cutting-edge and competitive in the fast-evolving landscape of artificial intelligence.
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Machine Learning Hardware jobs near you
Infographic showing various Machine Learning Hardware job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 97% Full Time, 1% Part Time, and 1% Contract. Highlights an 87% Physical, 10% Hybrid, and 3% Remote job distribution, with an average salary of $51,154 per year, or $24.6 per hour.
Machine Learning Engineer

Machine Learning Engineer

Qualcomm

San Diego, CA • On-site

Full-time

Posted 24 days ago

Job description

Job Summary:
Qualcomm Technologies, Inc. is a leading technology innovator that drives digital transformation to create a smarter, connected future. As a Machine Learning Engineer, you will develop and implement machine learning techniques and collaborate with cross-functional teams to enhance mobile, edge, auto, and IoT products.
Responsibilities:
• Applies Machine Learning knowledge to assist in extending training or runtime frameworks or model efficiency software tools with new features and optimizations.
• Assists in the modeling, architecture, and development of machine learning hardware (co-designed with machine learning software) for inference or training solutions.
• Assists in the development of optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with team members for joint design and development.
• Assists with the development and application of machine learning techniques into products and/or AI solutions to enable customers to do the same.
• Develops, adapts, or prototypes machine learning algorithms, models, or frameworks in alignment with product roadmap.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
Preferred:
• Master's degree in Computer Science, Engineering, Information Systems, or related field.
• 1+ year of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras).
• 1+ year of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media).
• 1+ year of experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++).
• 1+ year of experience using statistics and probability (e.g., conditional probability, Bayes rule).
• 1+ year of experience working in a large matrixed organization.
• 6+ months of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware.
Company:
Qualcomm designs wireless technologies and semiconductors that power connectivity, communication, and smart devices. Founded in 1985, the company is headquartered in San Diego, USA, with a team of 10001+ employees. The company is currently Late Stage.
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About Qualcomm

Sourced by ZipRecruiter

Qualcomm is enabling a world where everyone and everything can be intelligently connected. You interact with products and technologies made possible by Qualcomm every day, including 5G-enabled smartphones that double as pro-level cameras and gaming devices, smarter vehicles and cities, and the technology behind the smart, connected factories that manufactured your latest purchase. Our powerful connectivity solutions keep you connected—even in remote areas. Qualcomm 5G and AI innovations are the power behind the connected intelligent edge. You’ll find our technologies behind and inside the innovations that deliver significant value across multiple industries and to billions of people every day.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Diego, CA, US

Year founded

1985

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