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Ai Accelerator Jobs (NOW HIRING)

Honeywell

Director Embedded AI Engineering

Atlanta, GA · On-site

We are seeking someone with embedded AI experience, particularly with GPUs or AI accelerators, and strong system solution knowledge for AI application deployment. You will be part of the Forge and AI ...

Honeywell

Director Embedded AI Engineering

Atlanta, GA · On-site

We are seeking someone with embedded AI experience, particularly with GPUs or AI accelerators, and strong system solution knowledge for AI application deployment. You will be part of the Forge and AI ...

Honeywell

Director Embedded AI Engineering

Atlanta, GA · On-site

$126K - $166K/yr

We are seeking someone with embedded AI experience, particularly with GPUs or AI accelerators, and strong system solution knowledge for AI application deployment. You will be part of the Forge and AI ...

Maximus

Senior Director, AI Systems Engineering

VA · On-site +1

We are looking for an accomplished hands-on technical leader and team player to be a part of the AI Accelerator team. You will be responsible for architecting and optimizing scalable, secure AI ...

DensityAI

AI Core DV Engineer

Mountain View, CA · On-site

$180K - $320K/yr

Work with chip-design and software teams driving DensityAI's AI accelerator program from first silicon through scale-out. What you'll do * Own verification of our AI compute core - tensor pipelines ...

ERM

AI Solutions Engineer

Houston, TX

We're hiring AI Solutions Engineers to join our global AI Accelerator team - a small, highimpact group building practical, deployable solutions that consulting teams actually use. If you are someone ...

Erm

AI Solutions Engineer

Houston, TX

We're hiring AI Solutions Engineers to join our global AI Accelerator team - a small, highimpact group building practical, deployable solutions that consulting teams actually use. If you are someone ...

DensityAI

Compiler Engineer -- MLIR

Mountain View, CA · On-site

$200K - $360K/yr

About the role Own MLIR dialect design and lowering passes for our AI accelerator -- defining the high-level tensor IR, async / streaming semantics, and sharded-tensor types that bridge ML frameworks ...

DensityAI

DV Formal Verification

Mountain View, CA · On-site

$220K - $400K/yr

Work with chip-design and software teams driving DensityAI's AI accelerator program from first silicon through scale-out. What you'll do * Own block- and SOC-level formal verification, debug, and ...

DensityAI

SOC Design Verification

Mountain View, CA

$230K - $420K/yr

Work with chip-design and software teams driving DensityAI's AI accelerator program from first silicon through scale-out. What you'll do * Own SOC-level verification and emulation for our AI ...

Mythic

Senior Silicon Emulation Engineer

Austin, TX

$120K - $225K/yr

Develop and maintain emulation platforms for AI accelerator / AI-centric SoCs * Integrate large-scale RTL (compute, DMA, memory subsystems, interconnects) into emulation environments * Enable early ...

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Ai Accelerator information

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$38K

$52.8K

$66.5K

How much do ai accelerator jobs pay per year?

As of Jun 7, 2026, the average yearly pay for ai accelerator in the United States is $52,811.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,000.00 and $59,000.00 per year, depending on experience, location, and employer.

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

To thrive as an AI Accelerator, you need a deep understanding of machine learning algorithms, computer architecture, and parallel computing, often supported by a degree in computer science, electrical engineering, or a related field. Familiarity with hardware description languages (HDLs), CUDA, TensorFlow, and specific AI accelerator platforms is typically required. Strong problem-solving abilities, collaboration, and adaptability are essential soft skills for navigating complex projects and interdisciplinary teams. These skills and qualities are crucial for designing, optimizing, and deploying high-performance AI systems that meet real-world demands.

How does an AI Accelerator typically collaborate with data scientists and engineering teams on AI projects?

AI Accelerators work closely with both data scientists and engineering teams to bridge the gap between model development and deployment. They often help optimize AI models for efficiency and scalability, ensuring they run effectively on various hardware platforms. Regular collaboration includes reviewing model architectures, suggesting improvements for speed and accuracy, and troubleshooting performance bottlenecks together. This cross-functional teamwork is essential for translating research breakthroughs into robust, real-world AI solutions.

What are AI Accelerators?

AI Accelerators are specialized hardware or software systems designed to optimize and speed up artificial intelligence (AI) and machine learning (ML) workloads. They process complex computations required by AI algorithms more efficiently than general-purpose CPUs, enabling faster training and inference for deep learning models. Common examples of AI accelerators include GPUs, TPUs, FPGAs, and dedicated AI chips. These technologies are widely used in data centers, edge devices, and consumer electronics to support applications like image recognition, natural language processing, and autonomous vehicles.
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What cities are hiring for Ai Accelerator jobs? Cities with the most Ai Accelerator job openings:
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Ai Accelerator jobs near you
Infographic showing various Ai Accelerator job openings in the United States as of May 2026, with employment types broken down into 10% Internship, 70% Full Time, and 20% Part Time. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $52,811 per year, or $25.4 per hour.
Director Embedded AI Engineering

Director Embedded AI Engineering

Honeywell

Atlanta, GA • On-site

Full-time

Posted 4 days ago

Honeywell rating

8.3

Company rating: 8.3 out of 10

Based on 177 frontline employees who took The Breakroom Quiz

64th of 516 rated manufacturers

Job description

This role is for a hands-on lead specializing in Edge AI deployment. The successful candidate will provide specialized expertise in model optimization at the edge, robust deployment, and MLOps pipeline development. You will leverage your skills in edge optimization, system and embedded knowledge, AI/machine learning, MLOps, computer vision, innovation, and problem solving to drive advanced AI solutions.

We are seeking someone with embedded AI experience, particularly with GPUs or AI accelerators, and strong system solution knowledge for AI application deployment.

You will be part of the Forge and AI team, based in Atlanta, Georgia.

Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments - powered by our Honeywell Forge software - that help make the world smarter, safer and more sustainable.

YOU MUST HAVE

  • Proven experience in embedded AI with hands-on expertise in GPU or AI accelerator deployment.
  • Strong skills in edge model optimization and embedded system architecture.
  • Deep understanding of AI/machine learning algorithms and computer vision applications.
  • Experience building and managing MLOps pipelines for AI model deployment at the edge.
  • Excellent problem-solving skills and a passion for innovation in embedded AI technologies.

WE VALUE

  • Background in system solutions with AI application deployment experience.
  • Strong knowledge of embedded systems and real-time operating environments.
  • Experience working in collaborative, agile environments.
  • Advanced degree in Computer Science, Electrical Engineering, or related technical field preferred.

US PERSON REQUIREMENTS:

  • Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person which is defined as a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.

KEY RESPONSIBILITIES

  • Lead hands-on development and deployment of Edge AI solutions with a focus on model optimization and performance on embedded platforms.
  • Design and implement robust MLOps pipelines to support continuous integration and deployment of AI models at the edge.
  • Collaborate with cross-functional teams to integrate AI applications into embedded systems using GPUs and AI accelerators.
  • Provide technical leadership and mentorship in embedded AI, system architecture, and AI deployment strategies.
  • Drive innovation and problem-solving initiatives to enhance AI capabilities and deployment robustness on edge devices.

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Benefits

Hours and flexibility

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About Honeywell

Sourced by ZipRecruiter

Honeywell is charging into the Industrial IoT revolution with the establishment of Honeywell Connected Enterprise (HCE), building on our heritage of invention and deep, on-the-ground industry expertise. HCE is the leading industrial disruptor, building and connecting software solutions to streamline and centralize the assets, people and processes that help our customers make smarter, more accurate business decisions. Moving at the speed of software, we are creating, innovating and delivering solutions fast, challenging the way things have always been done, piloting new ways for all of us to work, and expecting our successes to set new standards for our customers and for Honeywell. The Chief Architect for Honeywell Connected Enterprise will lead a team of architects and system engineers responsible for the design of applications and infrastructure that deliver high value outcomes for customers in industrial, buildings, distribution centers, and aerospace vertical markets. The Chief Architect will work directly with leadership, development teams, and offering management to design well integrated solutions that utilize software platforming to encourage reuse and speed to market.

Industry

Furniture manufacturing

Company size

10,000+ Employees

Headquarters location

Charlotte, NC, US

Year founded

1906

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