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Ai Accelerator Jobs in Tennessee (NOW HIRING)

Oracle

Lead Principal Product Manager

Nashville, TN · On-site

Track and interpret shifts in the AI accelerator landscape (GPUs, custom silicon, emerging architectures) to shape where, when, and how OCI invests * Partner closely with engineering, hardware ...

Oracle

Lead Principal Product Manager

Nashville, TN · Hybrid

Track and interpret shifts in the AI accelerator landscape (GPUs, custom silicon, emerging architectures) to shape where, when, and how OCI invests * Partner closely with engineering, hardware ...

Oracle

Lead Principal Product Manager

Nashville, TN · Hybrid

Track and interpret shifts in the AI accelerator landscape (GPUs, custom silicon, emerging architectures) to shape where, when, and how OCI invests * Partner closely with engineering, hardware ...

Cyod

Principal AI Engineer

Nashville, TN · On-site

$180 - $240/hr

Mentor engineers and consultants while contributing reusable agentic design patterns, reference architectures, DevOps templates, and Google Cloud AI delivery accelerators for Insight. What We're ...

Insight Enterprises

Principal AI Engineer

Nashville, TN · On-site

$150 - $210/hr

Mentor engineers and consultants while contributing reusable agentic design patterns, reference architectures, DevOps templates, and Google Cloud AI delivery accelerators for Insight.What We're ...

Crowe LLP

Cyber AI Security Manager

Knoxville, TN · On-site +1

$105K - $143K/yr

Help establish reusable AI-enabled cybersecurity accelerators, patterns, and intellectual property that can be deployed across client engagements. Basic Qualifications * Minimum of 7 years ...

Crowe LLP

Cyber AI Security Manager

Nashville, TN · On-site +1

$107K - $144K/yr

Help establish reusable AI-enabled cybersecurity accelerators, patterns, and intellectual property that can be deployed across client engagements. Basic Qualifications * Minimum of 7 years ...

Humana

Lead Engineer - Technology Solutions

Nashville, TN · On-site

$99K - $130K/yr

Engineer and integrate automation, AI accelerators, and intelligent tooling to streamline workflows, reduce manual effort, and improve data quality. * Advance operational efficiency by supporting:

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Ai Accelerator information

What is an AI accelerator?

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.

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 does an AI accelerator do?

An AI accelerator is a professional who develops and optimizes hardware and software solutions to improve the performance of artificial intelligence models. They often work with specialized hardware like GPUs or TPUs and use programming skills in frameworks such as TensorFlow or PyTorch to enhance AI processing speed and efficiency.

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What job categories do people searching Ai Accelerator jobs in Tennessee look for?

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What cities in Tennessee are hiring for Ai Accelerator jobs?

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Ai Accelerator jobs near you
Infographic showing various Ai Accelerator job openings in Tennessee as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

AI Systems Engineer (OCI/AI Infrastructure)

Ll Oefentherapie

Nashville, TN • On-site

$120 - $180/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Oracle Hardware Platform Development Engineering is seeking a highly driven AI Systems Engineer to evaluate and characterize next-generation GPU and AI accelerator platforms for Oracle Cloud Infrastructure (OCI). This is a hands-on engineering role focused on bringing up new hardware platforms, enabling AI training and inference software stacks, running representative workloads, and analyzing system performance under real operating conditions.

The engineer will identify whether workloads are HBM/memory-bandwidth, compute, scale-up, or scale-out bound, while characterizing power, thermals, memory behavior, utilization, scaling, and performance efficiency. Working directly in the lab, you will debug hardware/software integration issues, design and execute experiments, and develop data-driven insights that explain system behavior beyond benchmark results.

A key part of the role is comparative architecture analysis across GPUs and emerging AI accelerators. You will evaluate architectural tradeoffs and translate performance findings into clear, actionable recommendations on which platforms are best suited for specific AI training and inference workloads. You will work closely with internal hardware and software teams as well as technology partners to help shape Oracle’s next generation of high-performance AI infrastructure.

Position Overview:

This position is ideal for someone who loves deep systems engineering, debugging complex hardware–software interactions, and optimizing performance at every layer of the ML stack. You will play a pivotal role in enabling the training and deployment of next-generation LLMs and generative AI models.

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