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Machine Learning Hardware Jobs (NOW HIRING)

IMC

Hardware Machine Learning Engineer

Chicago, IL

$127K - $167K/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 ...

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 · On-site

$145K - $191K/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 ...

Quantum Machines

Machine Learning Engineer

Chicago, IL · On-site

Through our pioneering hardware and software solutions based on instruction-based quantum control ... We are looking for a Machine Learning Engineer to design, build, and deploy machine learning ...

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Machine Learning Hardware information

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How much do machine learning hardware jobs pay per hour?

As of Jul 11, 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 engineer makes $500,000 a year?

Senior machine learning hardware engineers with extensive experience, specialized skills in hardware design, and advanced certifications can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or at top technology companies. These roles often require expertise in FPGA, ASIC design, or embedded systems, along with leadership responsibilities and a strong track record of innovation.

Which 3 jobs will survive AI?

For a Machine Learning Hardware professional, roles such as hardware design engineers, embedded systems engineers, and system architects are likely to persist as they require specialized knowledge of hardware development, integration, and optimization that AI cannot fully automate. These jobs involve complex problem-solving, hands-on hardware work, and understanding of physical components, making them less susceptible to automation by AI. Continuous learning of hardware tools and certifications can help maintain relevance in this evolving field.

Does machine learning involve hardware?

Machine learning hardware refers to the physical components like GPUs, TPUs, and specialized accelerators used to train and run machine learning models efficiently. Machine learning professionals often work with these hardware tools to optimize performance and reduce training time, making hardware an integral part of the field.

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 is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. These roles usually involve leadership responsibilities, extensive expertise, and may include stock options or bonuses as part of compensation.

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.

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.

More about Machine Learning Hardware jobs
What cities are hiring for Machine Learning Hardware jobs? Cities with the most Machine Learning Hardware job openings:
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Machine Learning Hardware jobs near you
Infographic showing various Machine Learning Hardware job openings in the United States as of July 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $51,154 per year, or $24.6 per hour.
Machine Learning Hardware Architect - Silicon

Machine Learning Hardware Architect - Silicon

Meta

Sunnyvale, CA

$212K/yr

Full-time

Posted 12 days ago

Meta rating

7.5

Company rating: 7.5 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

135th of 209 rated software companies

Job description

Meta’s mission is to give people the power to build community and bring the world closer together. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities — we're just getting started.Reality Labs (RL) focuses on delivering Meta's vision through Virtual Reality (VR) and Augmented Reality (AR). The compute performance and power efficiency requirements of Virtual and Augmented Reality require custom silicon. Reality Labs Silicon team is driving the state of the art forward with breakthrough work in computer vision, machine learning, mixed reality, graphics, displays, sensors, and new ways to map the human body. Our chips will enable AR & VR devices where our real and virtual world will mix and match throughout the day. We believe the only way to achieve our goals is to look at the entire stack, from transistors, through architecture, firmware, and algorithms. In this position you will work with Machine Learning Hardware Architects, Digital Designers, and Software engineers to develop custom Machine Learning Hardware accelerators for delivery into multiple SoCs. You will collaborate with a world-class group of researchers and architects to implement and contribute to the development and optimization of low power machine learning accelerators and state-of-the-art SoCs.
Machine Learning Hardware Architect - Silicon Responsibilities:
  • Technical lead for ML Hardware engineers, driving design from Architecture through to Product for AR/VR optimized silicon
  • Lead designs to surpass state of the art for metrics such as compute, bandwidth, and power consumption
  • Work across disciplines, brainstorm big ideas, work in new technology areas, juggle/coordinate multiple initiatives, drive a concept into a prototype and ultimately guide the transition into a high-volume consumer product
  • Travel both domestically and internationally

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 12+ years of experience as a Hardware Design Engineer or Silicon Architect for production silicon shipped in volume
  • Experience in Machine Learning IPs Silicon development
  • Experience in digital design µArchitecture, RTL coding
  • Experience with methods for partitioning a solution across hardware and software, evaluating trade-offs such as speed, performance, power, area
  • Results oriented, proactive with demonstrated creative & critical thinking

Preferred Qualifications:
  • Master/PhD degree in EE/CS or equivalent areas
  • Knowledge of Physical Design and Low power implementation
  • Experience with Firmware, DSP coding and optimization
  • Collaborate and/or lead in a team environment
  • Experience with SoC Architecture and subsystem Integration
  • Knowledge of industry trends and disruptive technologies
  • Experience in deep learning algorithms and techniques, e.g., convolutional neural networks, transformers, LLMs

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$212,000/year to $294,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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