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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 Inc

Hardware Machine Learning Engineer

Chicago, IL

$200K - $225K/yr

Hardware Machine Learning Engineer Chicago, United States; New York, United States We are deploying machine learning directly onto custom hardware - and we want you to help drive it from the ground ...

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

$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 ...

Qualcomm

Sr. Staff, Engineer

San Diego, CA · On-site

$110K - $152K/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: • ...

Qualcomm

LLVM / Ripple compiler Engineer

San Diego, CA · On-site

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: • ...

Qualcomm

Staff Engineer

San Diego, CA · On-site

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: • ...

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Machine Learning Hardware information

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How much do machine learning hardware jobs pay per hour?

As of Jun 21, 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 leading technology companies. These roles often require expertise in FPGA, ASIC design, or embedded systems, along with a strong understanding of machine learning workloads and hardware acceleration.

Which 3 jobs will survive AI?

For a Machine Learning Hardware professional, roles such as hardware design engineers, embedded systems engineers, and AI infrastructure specialists are likely to persist as they require specialized hardware knowledge, hands-on skills, and ongoing innovation. These jobs involve developing and maintaining the physical components that support AI systems, making them less susceptible to automation. Continuous learning in hardware architecture and certifications in relevant tools can enhance job security in this 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 hardware optimization, parallel processing, and high-performance computing environments to improve model performance and reduce training time.

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 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.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or executive positions, often requiring advanced skills in deep learning, data science, and experience with hardware acceleration. These roles may involve overseeing large projects, managing teams, or developing cutting-edge AI hardware and software solutions, and they usually offer compensation packages including salary, bonuses, and stock options. Such positions are rare and usually require extensive industry experience and specialized expertise in AI systems and hardware integration.
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Machine Learning Hardware jobs near you
Infographic showing various Machine Learning Hardware job openings in the United States as of June 2026, with employment types broken down into 97% Full Time, 2% Part Time, and 1% Temporary. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $51,154 per year, or $24.6 per hour.

Machine Learning Hardware Architect, TPU

Google

Sunnyvale, CA • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Google rating

8.8

Company rating: 8.8 out of 10

Based on 94 frontline employees who took The Breakroom Quiz

32nd of 191 rated software companies

Job description

Minimum qualifications:
  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
  • 10 years of experience in computer architecture or hardware engineering.
  • Experience with performance modeling, performance analysis, or hardware-software codesign.
  • Experience leading the architecture and technical direction for hardware or system-level projects.

Preferred qualifications:
  • Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
  • Experience in the architecture of high-performance AI accelerators.
  • Knowledge of system-level integration and deploying complex AI models on sophisticated hardware platforms.
  • Experience driving strategic technical initiatives and mentoring executive technical staff.

About the job
In this role, you'll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers Google's most demanding AI/ML applications. You'll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
As a Machine Learning Hardware Architect, you will influence the evolution of high-performance intelligence for next-generation computing infrastructure. You will have an opportunity to drive technology that powers large-scale systems where high throughput, reliability, and efficiency are mission-critical. You will be part of a team that pushes boundaries, developing solutions that define the future of intelligent data centers and enterprise hardware. You will contribute to the innovation behind products that transform industries, leveraging your expertise in system-level integration to deploy complex, large-scale AI models across sophisticated hardware platforms.
The AI and Infrastructure team is redefining what's possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving channel behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $192000 - $279000 (USD) 20% bonus target bonus equity benefits
Learn more about benefits at Google .
Responsibilities
  • Develop architectural specifications for next-generation high-performance computing systems.
  • Collaborate with software and systems teams to define requirements for AI workloads.
  • Perform architecture studies and drive performance, scalability, and power efficiency projections.
  • Influence technical roadmaps and provide strategic leadership for hardware-software platforms.
  • Drive cross-functional technical alignment across multiple engineering teams to ensure system-level integration.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy .
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

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