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Deep Learning Accelerator Jobs in Ohio (NOW HIRING)

SAP SE

$47 - $60.50/hr

Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed ... This is an expert role for architects who combine deep technical expertise with customer leadership ...

Core Specialty

IT Enterprise Architect

Cincinnati, OH · On-site

Enable engineering teams with reference implementations, templates, and accelerators * Security ... Deep expertise in Azure and/or AWS architectures (multi-region, high availability, DR/BCP design)

Core Specialty

IT Enterprise Architect

Cincinnati, OH · Hybrid

Enable engineering teams with reference implementations, templates, and accelerators * Security ... Deep expertise in Azure and/or AWS architectures (multi-region, high availability, DR/BCP design)

Finit

Implementation Architect

Cincinnati, OH · On-site

$79K - $106K/yr

Engage with client stakeholders to demonstrate a deep understanding of functional business ... Maintain inventory of key CPM scripts and solution accelerators. * Document Discovery/Requirements ...

Crowe LLP

Cyber AI Security Manager

Cleveland, OH · On-site +1

$107K - $145K/yr

You'll have the time, space, and support to go deep in your projects and build lasting technical ... Act as the security expert in designing, developing, and deploying secure AI and machine learning ...

Crowe LLP

Cyber AI Security Manager

Columbus, OH · On-site +1

$107K - $144K/yr

You'll have the time, space, and support to go deep in your projects and build lasting technical ... Act as the security expert in designing, developing, and deploying secure AI and machine learning ...

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Deep Learning Accelerator information

What is a deep learning accelerator?

Deep Learning Accelerators are specialized hardware or systems designed to speed up the processing and training of deep learning algorithms, such as neural networks. They are optimized for the heavy computational demands of tasks like image recognition, natural language processing, and other AI applications. Examples include Graphics Processing Units (GPUs), Tensor Processing Units (TPUs), and custom-designed chips like Application-Specific Integrated Circuits (ASICs) and Field-Programmable Gate Arrays (FPGAs). These accelerators enable faster data processing, lower power consumption, and improved efficiency compared to general-purpose CPUs. As AI applications grow, the use of deep learning accelerators is becoming increasingly important in both research and industry.

What skills and qualifications are needed to thrive as a deep learning accelerator engineer?

To thrive as a Deep Learning Accelerator Engineer, you need a strong background in computer engineering, digital design, and machine learning, typically supported by a degree in computer science or electrical engineering. Experience with hardware description languages (such as Verilog or VHDL), FPGA/ASIC toolchains, and familiarity with deep learning frameworks like TensorFlow or PyTorch is essential. Problem-solving, teamwork, and effective communication are crucial soft skills for collaborating with cross-functional teams and translating algorithmic requirements into efficient hardware solutions. These skills are vital to designing high-performance, energy-efficient hardware accelerators that advance AI capabilities and meet industry demands.

What are the main challenges faced when optimizing deep learning models for hardware accelerators?

One of the primary challenges in this role is bridging the gap between deep learning model requirements and the constraints of specialized hardware, such as GPUs, TPUs, or custom ASICs. This often involves model quantization, memory optimization, and adapting algorithms to exploit hardware parallelism while maintaining accuracy and efficiency. Collaboration with both hardware engineers and software developers is essential to ensure models run efficiently on target platforms, and staying current with evolving accelerator architectures is key to long-term success.

What is the difference between Deep Learning Accelerator vs Machine Learning Engineer?

AspectDeep Learning AcceleratorMachine Learning Engineer
Required CredentialsKnowledge of hardware design, FPGA/ASIC programming, deep learning frameworksDegree in Computer Science, Data Science, or related fields; experience with ML frameworks
Work EnvironmentHardware development labs, embedded systems, AI hardware companiesSoftware development environments, tech companies, research labs
Industry UsageAI hardware manufacturing, embedded AI solutionsAI/ML software development, data analysis, model deployment
Search & Comparison IntentFocus on hardware acceleration, AI hardware designFocus on software development, model building

Deep Learning Accelerators specialize in hardware design and optimization for AI workloads, working closely with hardware and embedded systems. Machine Learning Engineers develop and deploy ML models primarily through software, focusing on algorithms and data. While both roles involve AI, their core skills, work environments, and industry applications differ significantly.

Deep Learning Accelerator jobs near you
Infographic showing various Deep Learning Accelerator job openings in Ohio as of June 2026, with employment types broken down into 53% Full Time, and 47% Part Time. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Applied AI Engineer Intern - Summer 2027 (May/June Start)

Evendale, OH • On-site

GE Aerospace
Aerospace Product and Parts Manufacturing • 10K+ employees
Learn more about GE Aerospaceexternal

$20/hr

Full-time

Posted 12 days ago

GE Aerospace rating

8.8

Company rating: 8.8 out of 10

Based on 186 frontline employees who took The Breakroom Quiz

Job description

Job Description Summary
At GE Aerospace, our AI engineers don't just support projects - they help drive them. From day one, interns and co-ops take on real-world challenges, owning work from start to finish and building solutions that connect data, tools, cloud, AI, and engineering to advance the future of flight.
As an intern, you'll build expertise in cloud platforms, databases, data engineering, web design, Al technologies, and numerical methods to solve real-world engineering problems. Through hands-on projects, you'll work with the Innovator Method, Game Theory, and DecisionIQ, turning customer insights into impactful solutions. You'll have the opportunity to learn, contribute, and bring real business value and help shape the future of aerospace design.
Job Description
What You will Do
  • Develop technical solutions for engineers to evaluate and adopt data and AI solutions.
  • Consult on architecture, implement proof of concepts and deliver solutions for business strategic projects, including data science and machine learning systems.
  • Build and present product architectures, write technical code, and demo applications to stakeholders.
  • Gain hands-on experience with the Innovator Method, Game Theory, and DecisionIQ and turn customer insights into solution that deliver real business value.
  • Sharpen your skills in cloud platforms, databases, data engineering, web design, AI technologies, and numerical methods.
  • Use your strengths to support team members and build cross-functional relationships across the company.
  • Work to ship solutions to production that meet business needs and drive impact.

Our culture thrives on innovation, diversity, and deep collaboration. You'll contribute as both a learner and a builder, helping us push the design frontier in aerospace.
Qualifications
  • Currently enrolled in a Bachelor's degree program in Computer Science, Aerospace Engineering, Mechanical Engineering; or a related field at an accredited university or credentialed software accelerator program.
  • Minimum 3.7 cumulative GPA off a 4.0 scale without rounding

No prior work experience is required.
Desired Characteristics
  • Strong academic performance in Computer Science or other STEM disciplines
  • Experience designing AI solutions and architecting distributed data systems
  • Proficiency in programming and debugging with Python, C#, C++, and SQL
  • Customer-centric mindset with ability to lead design thinking workshops
  • Hands-on experience in at least one of the following areas: Machine Learning, Large Language Models (LLMs), or Computer Vision
  • Experience building solutions using public cloud platforms such as AWS or Azure
  • AWS and/or Azure certification

About The Internship
  • Location: Remote
  • Pay rates for this position begin at $20/hour and increase for each undergraduate year completed. Relocation support and housing assistance is available for those who relocate to a new city.
  • Travel Opportunities
  • Real-world project ownership
  • Mentorship from experienced engineers
  • Opportunity for return offers

Equal Opportunity Employer
GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation. GE Aerospace is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
#LI-Remote - This is a remote position
Additional Information
GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation. GE Aerospace is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE Aerospace will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable). Employees may also be subject to random and reasonable-suspicion drug and alcohol testing.
Relocation Assistance Provided: No
#LI-Remote - This is a remote position

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