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Ai Hardware Engineer Jobs (NOW HIRING)

Head of Hardware Design

San Francisco, CA · On-site

$245K - $270K/yr

To do this, we're building the world's first AI hardware engineer. Founded in 2019, our platform enables anyone to go from idea to manufacturable board using nothing more than a natural language ...

Hardware Systems Engineer, NPI AI Responsibilities: * Lead end-to-end system validation strategies for AI and HPC hardware platforms, including AI accelerators, GPU clusters, and high-bandwidth ...

Hardware Engineer

San Jose, CA · On-site

$91K - $121K/yr

As AI scales, so does data. Every interaction, every model, every system generates data that must ... Hardware Development Engineering Build the hardware behind the world's data. As a Hardware ...

Hardware Engineer

San Jose, CA · On-site

$144K - $191K/yr

As AI scales, so does data. Every interaction, every model, every system generates data that must ... Hardware Development Engineering Build the hardware behind the world's data. As a Hardware ...

New

Hardware Engineer

San Jose, CA

$144K - $191K/yr

As AI scales, so does data. Every interaction, every model, every system generates data that must ... Hardware Development Engineering Build the hardware behind the world's data. As a Hardware ...

New

Hardware Engineer

San Mateo, CA · On-site

$140K - $185K/yr

Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the ... About this Role As a Hardware Engineer on our hardware team, you will lead the design and ...

Hardware Engineer

Sunnyvale, CA · On-site

$185K - $247K/yr

The Role We are seeking an experienced Hardware Engineer to join our Hardware team and play a key ... Experience designing hardware for AI/ML workloads or high-performance computing systems

Hardware Engineer

Sunnyvale, CA · Hybrid

$185K - $247K/yr

The Role We are seeking an experienced Hardware Engineer to join our Hardware team and play a key ... Experience designing hardware for AI/ML workloads or high-performance computing systems

Your work has the potential to shape the compute hardware and AI hardware going into our cutting-edge data centers affecting billions of users. Meta is seeking a motivated Power Engineer to join our ...

Head of Hardware

Palo Alto, CA

$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 ...

Hardware Engineer

Sterling, VA · On-site

$100K - $115K/yr

Join Us as a Hardware Design Engineer! Are you ready to make a significant impact in an innovative ... Leverage AI-enabled tools and automation to support daily tasks and productivity. * Commitment to ...

Senior Hardware Engineer

Saratoga, CA · On-site

$210K - $265K/yr

Today's AI performance is frequently limited by communication bottlenecks. Eridu delivers multiple ... Visit our website eridu.ai to learn mo Position Overview As a Hardware Engineer in our Systems ...

This role sits at the center of cutting-edge AI hardware development, keeping the servers, PCIe systems, and engineering infrastructure running that power next-generation compute. You'll be hands-on ...

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Ai Hardware Engineer information

See salary details

$51K

$146.2K

$196.5K

How much do ai hardware engineer jobs pay per year?

As of Aug 4, 2026, the average yearly pay for ai hardware engineer in the United States is $146,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,500.00 and $163,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI hardware engineer, and why are they important?

To thrive as an AI Hardware Engineer, you need strong foundations in computer engineering, digital logic design, and knowledge of machine learning algorithms, typically supported by a degree in electrical engineering or computer engineering. Familiarity with hardware description languages (such as Verilog or VHDL), FPGA/ASIC development tools, and experience with simulation and debugging systems are essential. Problem-solving abilities, attention to detail, and effective teamwork are standout soft skills for this role. These skills are crucial for creating efficient, reliable AI hardware solutions and collaborating across multidisciplinary teams to advance cutting-edge technologies.

What is an AI hardware engineer?

AI Hardware Engineers are professionals who design, develop, and optimize computer hardware systems specifically for artificial intelligence applications. Their work involves creating specialized processors, such as GPUs, TPUs, or custom chips, that accelerate machine learning tasks and handle large-scale data processing efficiently. They collaborate with software engineers to ensure hardware and AI models work seamlessly together, improving performance, power efficiency, and scalability of AI systems. AI Hardware Engineers play a crucial role in advancing technologies used in data centers, autonomous vehicles, robotics, and edge devices.

What is the difference between Ai Hardware Engineer vs AI Software Engineer?

AspectAi Hardware EngineerAI Software Engineer
Required CredentialsBachelor's in Electrical Engineering, Computer Engineering, or related fields; knowledge of hardware design and programmingBachelor's or higher in Computer Science, Software Engineering, or related; proficiency in programming languages and AI frameworks
Work EnvironmentDesigning, testing, and developing AI hardware components in labs or manufacturing settingsDeveloping AI algorithms and applications in software development environments
Employer & Industry UsageTech companies, hardware manufacturers, research labsSoftware firms, tech startups, AI research organizations

While both roles focus on AI, Ai Hardware Engineers specialize in creating the physical components that enable AI systems, whereas AI Software Engineers develop the algorithms and software that run on hardware platforms. Understanding these differences helps job seekers target the right roles based on their skills and interests.

How do AI hardware engineers typically collaborate with software and data teams during the development process?

AI Hardware Engineers work closely with software developers and data scientists to ensure that hardware architectures are optimized for specific AI workloads. Collaboration often involves regular meetings to discuss performance requirements, compatibility challenges, and customizations needed for machine learning models. By maintaining open communication channels, hardware engineers can adapt designs based on feedback from software and data teams, ensuring seamless integration and optimal system performance.
More about Ai Hardware Engineer jobs
What cities are hiring for Ai Hardware Engineer jobs? Cities with the most Ai Hardware Engineer job openings:
What states have the most Ai Hardware Engineer jobs? States with the most job openings for Ai Hardware Engineer jobs include:
What job categories do people searching Ai Hardware Engineer jobs look for? The top searched job categories for Ai Hardware Engineer jobs are:
Infographic showing various Ai Hardware Engineer job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $146,230 per year, or $70.3 per hour.

Head of Hardware Design

Flux

San Francisco, CA • On-site

$245K - $270K/yr

Full-time

Re-posted 13 days ago


Job description

Why Flux

Flux is taking the hard out of hardware. To do this, we’re building the world's first AI hardware engineer. Founded in 2019, our platform enables anyone to go from idea to manufacturable board using nothing more than a natural language prompt. This democratizes a process that has historically required years of specialized expertise.
We're going after a $15B+ electronic design automation market, backed by 8VC, Bain Capital Ventures, Liquid 2 Ventures, Outsiders Fund, Figma board member John Lilly, and GitHub founder Tom Preston-Werner. In February 2026, we closed a total of $37M in funding to accelerate that mission.
What happens when we unlock the ability for anyone to make hardware? We fundamentally reshape the world. That's our mission, and we're just getting started.

The Role

We’re looking for an experienced electrical engineering leader who will own the hardware design practices and guiding principles of our platform. You’ll steer the evolution of our ECAD tool's core capabilities as well as the correctness of our AI Hardware Engineer's system knowledge and design approach. You'll actively partner with product leadership to shape and prioritize AI capability development, evaluation frameworks, and in developing scaled approaches to guide our community to successful PCB projects. In this role, you'll grow our existing Hardware Design function and team.

This is a high‑impact, multidisciplinary role for someone who has experience building complex electronics that shipped at scale (e.g., smartphones, wearables, high‑performance compute, networking, robotics) and loves translating real‑world engineering constraints into powerful tools and AI behaviors.

What you’ll do
  • Drive ECAD feature design & specs – Craft product requirements for core ECAD behaviors across placement/routing, constraints management, stackup, impedance control, DRC/DFM, manufacturing outputs, and prototyping workflows. Co-author specs, validate by running dogfooding initiatives, beta programs, and scaled user feedback.

  • Be the design partner to AI/ML – Teach the world’s first AI hardware engineer how to design successful products. Define best practices, guardrails, and evaluation harnesses; curate datasets; review AI‑generated designs; create the AI expertise that will help more people build successful hardware on their first production run, without releasing the magic smoke.

  • Build out the Hardware Design function – Start as a hands‑on manager with two existing reports. Over time, refine the team's core responsibilities, and build a larger team that produces reference designs, demos, product specs, training, and field feedback loops.

  • Develop real hardware – Lead quick‑turn-around prototypes (from schematic to bring‑up) that exercise product/AI capabilities. Instrument designs for SI/PI and power/thermal validation; close the loop with data.

  • Amplify user insight – Adopt ownership and improve upon current user experience signals, feedback loops, and channeling user input into our iterative product design. Strategically invest in deeper customer relationships. Champion the user’s voice in cross‑functional forums. Partner closely with our software engineering department in ensuring AI evaluations are reflective of real-world user requirements.

  • Product – Be the "voice of the customer" within the organization, addressing vision, strategy, research & discovery, prioritization and cross-functional leadership.

What you’ll bring
  • Deep EE breadth + depth with real products in the field. Comfortable spanning:

    • RF & wireless: from sub‑GHz to mmWave; matching, filtering, antenna/feed layout.

    • EMI/EMC & ESD: design‑for‑compliance, grounding/return paths, shielding, filtering.

    • Power electronics: DC‑DC (buck/boost), PMICs, PoE, motor/actuator control, power sequencing, efficiency/thermal trade‑offs.

    • Analog & mixed‑signal: sensor interfaces, data converters, low‑noise design.

    • High‑speed digital: DDRx, PCIe/SerDes, USB‑C/USB4, MIPI, Ethernet (1G–25G+); timing, skew, and equalization considerations.

    • SI/PI: signal/power integrity analysis, decoupling strategies, return‑path control.

  • PCB/stackup expertise: material selection and stackup definition, controlled impedance, differential pair tuning & length‑matching, via strategies (blind/buried, microvia, backdrill), HDI (high‑density interconnect), panelization, and build rules with fabs/EMS.

  • DFM/DFT & manufacturing: hands‑on bring‑up and debug, test coverage, fixture definition; tight collaboration with CMs/ODMs.

  • Tooling fluency: meaningful time in multiple ECADs (e.g., Altium, Cadence Allegro/OrCAD, Mentor Xpedition, KiCad, Zuken) and experience with simulation tools (SPICE, SI/PI such as ADS/HyperLynx/SIwave; 3D EM such as HFSS), plus lab instrumentation (oscilloscope, VNA, logic analyzer, power analyzer).

  • Product sense & communication: ability to turn messy user needs into simple workflows; excellent written specs, diagrams, and presentations; confident with senior leadership and deep‑dive technical reviews.

  • Leadership at multiple altitudes: thrive as both a hands‑on engineer and a manager; co-develop core ECAD product strategy. Hire, mentor, and scale processes while staying close to the work.

Preferred qualifications
  • Experience in a larger technical org (e.g., hardware product management or lead EE for critical subsystems at a world‑class company) with a track record of shipping at scale.

  • On the ground factory and test, mass production, and quality/yield optimization experience. Actively participating in builds and carrying key responsibilities to realize designs at scale.

  • Prior design‑partner or customer‑facing role (product management, applications, FAEs, field engineering, or cross‑functional liaison) that turned feedback into product wins.

  • Hands‑on across ECAD platforms; passion for great engineering tools and workflows.

  • Practical exposure to AI/ML (prompting/evaluation, data curation/labeling, or integrating ML‑assisted design tools).


Benefits & package

Competitive salary and meaningful equity, plus comprehensive benefits. Title/level will match experience and impact.


How to apply

Send a your resume, a quick cover letter, and any links to public designs or talks.
Email: hiring@flux.ai
Subject: Head of Hardware Design – Your Name

Flux is an equal opportunity employer. We are committed to providing equal employment opportunities to all qualified individuals and do not discriminate on the basis of race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable federal, state, or local law. All employment decisions are based on qualifications, merit, and business need.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Compensation Range: $245K - $270K