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Deep Learning Accelerator Jobs in Decatur, GA (NOW HIRING)

Deep familiarity with AWS services (Lambda, ECS/EKS, S3, API Gateway) and Infrastructure as Code ... You view AI as an accelerator, not a replacement for good design. You possess the ability to review ...

Sr Advanced AI Platform Engineer

Atlanta, GA · On-site

$117K - $155K/yr

You will work at the intersection of data engineering, machine learning operations, and edge AI ... Deep hands-on experience with cloud-native data platforms (Databricks, BigQuery, Azure Data Lake ...

Apply deep gas utility domain expertise - covering distribution, transmission, and storage ... Our always-on learning agenda drives their continuous improvement through building and transferring ...

Sr Advanced AI Platform Engineer

Atlanta, GA · On-site

$117K - $155K/yr

You will work at the intersection of data engineering, machine learning operations, and edge AI ... Deep hands-on experience with cloud-native data platforms (Databricks, BigQuery, Azure Data Lake ...

This role is designed as a career accelerator --our goal is to train you to eventually become a ... We value the deep medical knowledge FMGs bring and the practical, hands-on efficiency of MAs and ...

Showing results 41-60

Deep Learning Accelerator information

See Decatur, GA salary details

$10.7K

$81.9K

$136.7K

How much do deep learning accelerator jobs pay per year?

As of Sep 11, 2026, the average yearly pay for deep learning accelerator in Decatur, GA is $81,900.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,300.00 and $135,700.00 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.

Infographic showing various Deep Learning Accelerator job openings in Decatur, GA as of June 2026, with employment types broken down into 2% Internship, 5% As Needed, 65% Full Time, 26% Part Time, and 2% Summer. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $81,900 per year, or $39.4 per hour.

Director, SAP S4 Public Cloud Delivery Lead

Atlanta, GA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.


Key responsibilities

  • Oversee end-to-end delivery of SAP S/4HANA Public Cloud R2R programs, ensuring on-time, on-budget execution and providing strategic guidance across design, build, testing, cutover, and hyper care.

  • Lead business development activities by identifying opportunities, shaping delivery strategy, and presenting SAP S/4HANA Public Cloud solutions aligned with client goals.

  • Collaborate with enterprise architecture teams to design future-state R2R solutions leveraging SAP BTP, Datasphere, SAC, and AI/ML for real-time reporting, predictive insights, and compliance.


Job description

The KPMG Advisory practice is at the forefront of transformation, offering excellent opportunities for individuals to advance their careers and expertise with KPMG. Looking ahead, we anticipate continued evolution and success within the practice, fostering both personal and professional development, thereby creating new pathways for growth. In this ever-changing market environment, our professionals must be adaptable and thrive in a collaborative, team-driven culture. At KPMG, our people are our number one priority. With a wealth of learning and career development opportunities, a world-class training facility, and leading market tools, we help our people continue to grow both professionally and personally. If you're looking for a firm with a strong team connection where you can be your whole self, have an impact, advance your skills, deepen your experiences, and have the flexibility and access to constantly find new areas of inspiration and expand your capabilities, then consider a career in Advisory.
KPMG is currently seeking a Director, SAP S4 Public Cloud Delivery Lead to join our Advisory Services practice
Responsibilities:
  • Drive business development by identifying R2R opportunities, shaping delivery strategy, crafting proposals, and presenting SAP S/4HANA Public Cloud solutions aligned with client goals for financial close, consolidation, and reporting modernization
  • Lead ERP tool selection and implementation planning through finance process assessments, business case development, and roadmap creation; ensure readiness for R2R capabilities including Universal Journal, Group Reporting, and Financial Close
  • Oversee end-to-end delivery of SAP S/4HANA Public Cloud R2R programs, ensuring on-time, on-budget execution; provide strategic guidance across design, build, testing, cutover, and hyper care, while managing global teams and advising on key finance decisions
  • Collaborate with enterprise architecture teams to design future-state R2R solutions leveraging SAP BTP, Datasphere, SAC, and AI/ML for real-time reporting, predictive insights, and compliance across financial processes
  • Drive pricing strategy and manage project financials including forecasting, billing, and margin optimization; align delivery outcomes with finance performance goals such as close cycle reduction and reporting accuracy
  • Promote R2R delivery innovation through accelerators and methodology refinement; lead high-performing teams, foster career development, and cultivate a culture of ownership, collaboration, and continuous improvement
  • Act with integrity, professionalism, and personal responsibility to uphold KPMG's respectful and courteous work environment

Qualifications:
  • Minimum ten years of recent experience in managing large-scale SAP programs, including at least two full lifecycle SAP S/4HANA Public Cloud R2R implementations in Professional Services industry; strong track record in risk mitigation, issue resolution, and coordination across finance, consolidation, and reporting workstreams
  • Bachelor's degree from an accredited college or university in an appropriate field
  • Proven experience leading sales pursuits for SAP S/4HANA Public Cloud R2R programs, including shaping delivery strategy, defining scope, and presenting finance transformation solutions aligned with goals for financial close acceleration, reporting automation, and compliance; extensive experience conducting finance process assessments, building business cases, and developing R2R transformation roadmaps; skilled in guiding clients through delivery planning and execution aligned with financial reporting and regulatory objectives
  • Demonstrated success in leading full R2R delivery lifecycle including chart of accounts design, Universal Journal setup, build, testing, cutover, and hypercare; proven ability to manage global finance teams and ensure excellence across functional, technical, and integration domains; deep understanding of SAP S/4HANA Public Cloud R2R architecture and integration with enterprise finance systems; experience with SAP BTP, Datasphere, and SAC for reporting and consolidation; skilled in pricing strategy and project financials including forecasting, billing, and margin optimization
  • Track record of driving R2R delivery innovation through accelerators and methodology refinement; strong ability to engage senior finance stakeholders, align delivery with performance goals, and lead diverse teams in a collaborative, growth-oriented environment
  • Excellent verbal and written communication skills, with the ability to produce client-ready deliverables and thought leadership content at publication quality
  • Travel as needed

KPMG LLP and its subsidiaries ("KPMG") complies with all local/state regulations regarding displaying salary ranges. If required, the ranges displayed below or via the URL below are specifically for those potential hires who will work in the location(s) listed. Any offered salary is determined based on relevant factors such as applicant's skills, job responsibilities, prior relevant experience, certain degrees and certifications and market considerations. In addition, KPMG is proud to offer a comprehensive, competitive benefits package, with options designed to help you make the best decisions for yourself, your family, and your lifestyle. Available benefits are based on eligibility. Our Total Rewards package includes a variety of medical and dental plans, vision coverage, disability and life insurance, 401(k) plans, and a robust suite of personal well-being benefits to support your mental health. Depending on job classification, standard work hours, and years of service, KPMG provides Personal Time Off per fiscal year. Additionally, each year KPMG publishes a calendar of holidays to be observed during the year and provides eligible employees two breaks each year where employees will not be required to use Personal Time Off; one is at year end and the other is around the July 4th holiday. Additional details about our benefits can be found towards the bottom of our KPMG US Careers site at Benefits & How We Work .
Follow this link to obtain salary ranges by city outside of CA:
https://kpmg.com/us/en/how-we-work/pay-transparency.html/?id=M132ADV_2_26 California Salary Range: $184870 - $324185
KPMG offers a comprehensive compensation and benefits package. KPMG is an equal opportunity employer. KPMG complies with all applicable federal, state and local laws regarding recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, citizenship status, disability, protected veteran status, or any other category protected by applicable federal, state or local laws. The attached link contains further information regarding KPMG's compliance with federal, state and local recruitment and hiring laws. No phone calls or agencies please.
KPMG recruits on a rolling basis. Candidates are considered as they apply, until the opportunity is filled. Candidates are encouraged to apply expeditiously to any role(s) for which they are qualified that is also of interest to them.
Los Angeles County applicants: Material job duties for this position are listed above. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, and safeguard business operations and company reputation. Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.