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Deep Learning Accelerator Jobs in Chicago, IL (NOW HIRING)

Engineer II, Software

Niles, IL ยท On-site

$90K - $145K/yr

Hardware deep learning accelerators Applicants for this position must be currently authorized to work in the United States on a fullโ€‘time basis. Shure will not sponsor applicants for this position ...

Engineer II, Software

Niles, IL ยท On-site

$98K - $134K/yr

Hardware deep learning accelerators Applicants for this position must be currently authorized to work in the United States on a full-time basis. Shure will not sponsor applicants for this position ...

Engineer II, Software

Niles, IL ยท On-site

$98K - $134K/yr

Hardware deep learning accelerators Applicants for this position must be currently authorized to work in the United States on a full-time basis. Shure will not sponsor applicants for this position ...

Engineer II, Software

Niles, IL

$98K - $134K/yr

Hardware deep learning accelerators Applicants for this position must be currently authorized to work in the United States on a full-time basis. Shure will not sponsor applicants for this position ...

Engineer II, Software

Niles, IL ยท On-site

$98K - $134K/yr

Hardware deep learning accelerators Applicants for this position must be currently authorized to work in the United States on a full-time basis. Shure will not sponsor applicants for this position ...

Software Engineering Intern

Niles, IL ยท On-site

$23 - $43/hr

Hands-on experience with one or more of the following is a plus: * real-time digital signal processing * embedded Linux development * deep learning model deployment * GPU or hardware accelerators.

Software Engineering Intern

Niles, IL ยท Hybrid

$23 - $43/hr

Hands-on experience with one or more of the following is a plus: * real-time digital signal processing * embedded Linux development * deep learning model deployment * GPU or hardware accelerators.

Software Engineering Intern

Niles, IL ยท On-site

$23 - $43/hr

Hands-on experience with one or more of the following is a plus: * real-time digital signal processing * embedded Linux development * deep learning model deployment * GPU or hardware accelerators.

Software Engineering Intern

Niles, IL ยท Hybrid

$23 - $43/hr

Hands-on experience with one or more of the following is a plus: * real-time digital signal processing * embedded Linux development * deep learning model deployment * GPU or hardware accelerators.

Software Engineering Intern

Niles, IL ยท Hybrid

$23 - $43/hr

Hands-on experience with one or more of the following is a plus: * real-time digital signal processing * embedded Linux development * deep learning model deployment * GPU or hardware accelerators.

High Level RF Engineer

Batavia, IL ยท On-site

$88K - $116K/yr

... learning of particle accelerator systems. What your day-to-day as a High-Level RF Engineer at ... We support discovery science experiments in Illinois and locations around the world, including deep ...

Paid Media Manager

Chicago, IL ยท On-site

$108K - $141K/yr

Accelerator is Mars Snacking's growth engine, focused on unlocking growth across high-potential ... Learning, Innovation & Cross-Functional Leadership - Champion a culture of testing and learning ...

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Deep Learning Accelerator information

See Chicago, IL salary details

$11.3K

$86.4K

$144.2K

How much do deep learning accelerator jobs pay per year?

As of Sep 10, 2026, the average yearly pay for deep learning accelerator in Chicago, IL is $86,414.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,200.00 and $143,200.00 per year, depending on experience, location, and employer.

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.

Engineer II, Software

Niles, IL โ€ข On-site

Shure
Computer and Electronic Product Manufacturingย โ€ขย 1 - 5K employees

$90K - $145K/yr

Other

Medical, Retirement, PTO

Re-posted 28 days ago


Job description

Overview

Join Shureโ€™s Video and Emerging Data Technology team and help shape the next generation of intelligent audio, video, and collaboration solutions.

As an Engineer II, Software, you will play a critical role in transforming cuttingโ€‘edge AI/ML research into scalable, productionโ€‘ready technologies that power realโ€‘world products used by customers around the globe. From developing advanced machine learning models and dataโ€‘driven systems to optimizing algorithms for deployment across cloud, edge, and embedded platforms, youโ€™ll work at the intersection of innovation and product development.

Partnering closely with research scientists, signal processing engineers, data engineers, and crossโ€‘functional teams, youโ€™ll help bring emerging technologies from concept to commercialization while influencing the future direction of Shureโ€™s technology portfolio.

This position will be hybrid, based out of our Niles, IL HQ.

Responsibilities
  • Collaborate: work as part of a crossโ€‘functional team to create, design & implement cuttingโ€‘edge features and products
  • Ideate: brainstorm with research scientists and other stakeholders to identify use cases of value to Shure customers empowered by AI/ML and opportunities to optimize and platform solutions
  • Conduct Research: survey literature and conduct original research and experiments to optimize implementation strategies and characteristics, solve problems, share findings and prototypes with colleagues, senior staff, and executives
  • Identify Software Requirements: in collaboration with AI/ML research scientists, other software engineers, and product managers. Identify and document architectural options and opportunities for platforming and reuse including working research scientists to standardize platformed solutions to frameworks and software deployments
  • Implement Prototypes: software features in diverse areas from embedded (primary) to mobile apps, desktop, cloud, and database applications. Suggest subjectโ€‘matterโ€‘relevant features and other software opportunities to enhance research scientistsโ€™ chances of success (e.g. DSP approaches)
  • Develop Product Software Features: Implement, optimize, and test software applications and functionalities for realโ€‘time, semiโ€‘latent, and offline applications. Work with research scientists to identify and optimize input features, frame rates, model structures, and other characteristics that impact implementation characteristics
  • Evaluate: Validate implemented AI/ML and other algorithm features: write software to automate measurement of AI and algorithmic features against defined metrics
  • Lead: Mentor, coach, and monitor the work of less experienced engineers
  • Follow Coding Best Practices: Participate in code reviews and provide constructive feedback to peers
  • Stay Current in Field: track progress in software methodologies, tools, and best practices
  • Participate in Working Groups: to promote collaborative problem solving in specific areas, sometimes tangential to your expertise
  • Design and Document Software Approach: in collaboration with team (or on own in independent projects) documented in collaborative systems
  • Invent: contribute to intellectual property, participate in brainstorming, and encourage general innovation in the group
Qualifications
  • Bachelorโ€™s degree in computer science, computer engineering or related field; with minimum 2 years of related experience OR Masterโ€™s degree
  • Must have: Proficiency in C++
  • Proficiency in one or more other high level programing languages such as Python, Rust, Java, etc
  • Proficiency in software development principles, design patterns, and objectโ€‘oriented design methodology, multiโ€‘thread realโ€‘time application
  • Experience with embedded software development, Mac & PC application development, mobile apps, or cloudโ€‘based applications and services
  • Working knowledge of signal processing, computer vision, and machine learning
  • Experience with any of the following highly desirable:
    • Real time video applications: processing, encoding, transmission, etc
    • Embedded Linux or AOSP development
    • GPU programming
    • Hardware deep learning accelerators

Applicants for this position must be currently authorized to work in the United States on a fullโ€‘time basis. Shure will not sponsor applicants for this position for work visas.

Compensation

Base salaries vary based on qualifications, geography, experience, and expertise in each respective discipline. The range displayed on each job posting reflects the minimum and maximum base salary for the opportunity. The base salary for this position ranges from $90,600 to $145,000. If your salary expectations do not align, still apply as we are often flexible on the seniority of posted positions. All positions also include an awardโ€‘winning benefits package.

Benefits

At Shure, we prioritize the wellโ€‘being of our Associates. We offer competitive rewards packages to fullโ€‘time and partโ€‘time Associates working 24 or more hours a week that address physical, mental, financial, and overall wellโ€‘being. Our benefits include comprehensive healthcare, mental health and retirement savings plans, generous paid time off programs, employee discounts, professional development opportunities, workโ€‘life balance initiatives, employee recognition programs, and volunteering/community involvement opportunities.

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