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 ...
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 ...
Machine Learning Hardware Architect - Silicon
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$212K - $294K/yr
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 ...
Machine Learning Hardware Architect - Silicon
Sunnyvale, CA · On-site
$212K - $294K/yr
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 ...
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$141 - $211/hr
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:
Machine Learning Compiler
Manhattan, NY · On-site
$141 - $211/hr
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:
Machine Learning Compiler
Manhattan, NY · On-site
$141 - $211/hr
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 ...
New
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$141 - $211/hr
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New
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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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New York, NY · On-site
$140K - $211K/yr
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Chicago, IL · On-site
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Chicago, IL · On-site
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AI Hardware Systems Engineer, Annapurna Labs, Trainium Machine Learning Fleet Operations
Austin, TX · On-site
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Austin, TX · On-site
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Chicago, IL · On-site
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Quick apply
Head of Hardware
Palo Alto, CA · On-site
$145K - $191K/yr
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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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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 pr...
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AI Hardware Systems Manager, Annapurna Labs, Trainium Machine Learning Fleet Operations
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San Francisco, CA · On-site
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Post-Silicon Systems Software Validation Engineer
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AI Hardware Systems Manager, Annapurna Labs, Trainium Machine Learning Fleet Operations
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Austin, TX · On-site
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$110 - $165/hr
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Machine Learning Engineer
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Machine Learning System Hardware Architect
Sunnyvale, CA · On-site
$285K/yr
Proven track record 5+ years architecting hardware solutions for Machine Learning, acceleration and optimization. * Experience with deep learning frameworks including TensorFlow, PyTorch ...
Machine Learning System Hardware Architect
Sunnyvale, CA · On-site
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Proven track record 5+ years architecting hardware solutions for Machine Learning, acceleration and optimization. * Experience with deep learning frameworks including TensorFlow, PyTorch ...
Machine Learning Hardware information
See salary details
$12.26 - $15.52
9% of jobs
$17.67 is the 25th percentile. Wages below this are outliers.
$15.52 - $18.77
25% of jobs
The median wage is $21.58 / hr.
$18.77 - $22.03
19% of jobs
$22.03 - $25.28
18% of jobs
$26.39 is the 75th percentile. Wages above this are outliers.
$25.28 - $28.54
12% of jobs
$28.54 - $31.80
10% of jobs
$31.80 - $35.05
6% of jobs
$35.05 - $38.31
1% of jobs
$38.31 - $41.56
0% of jobs
$41.56 - $44.82
0% of jobs
$44.82 - $48.08
0% of jobs
$12
$24
$48
How much do machine learning hardware jobs pay per hour?
What is a machine learning hardware?
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 cities are hiring for Machine Learning Hardware jobs?
Cities with the most Machine Learning Hardware job openings:
What are the most commonly searched types of Machine Learning Hardware jobs?
The most popular types of Machine Learning Hardware jobs are:
What job categories do people searching Machine Learning Hardware jobs look for?
The top searched job categories for Machine Learning Hardware jobs are:
- Machine Learning Biomedical Engineer
- Machine Learning Engineer Python
- Senior Meta Machine Learning
- Mlops Machine Learning Engineer
- Remote Tesla Machine Learning Engineer
- Computer Vision Deep Learning
- Machine Learning Engineer Two
- Graduate Machine Learning Engineer
- Home Based Nvidia Machine Learning
- Full Time No Experience Machine Learning

$212K/yr
Full-time
Re-posted 23 days ago
Meta rating
7.8
Based on 45 frontline employees who took The Breakroom Quiz
137th of 245 rated software companies
Job description
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 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.
About Meta
Sourced by ZipRecruiter
Industry
Internet and it, media and telecom and software development
Company size
10,000+ Employees
Headquarters location
Menlo Park, CA, US