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Embedded Ai Engineer Jobs in Atlanta, GA (NOW HIRING)

Hands-On AI Security Engineering Actively contribute to architecture, design, and development of AI/ML and GenAI systems with embedded security controls. Integrate security across the SSDLC ...

AI Product Strategy Director

Atlanta, GA · On-site

$165K - $297K/yr

Embedded within the CDIO Executive Office, this leader uses AI-assisted software development to ... The ideal candidate is an experienced software engineer, AI developer, startup builder, or ...

AI Product Strategy Director

Atlanta, GA · On-site

$165K - $297K/yr

Embedded within the CDIO Executive Office, this leader uses AI-assisted software development to ... The ideal candidate is an experienced software engineer, AI developer, startup builder, or ...

Systems Engineer

Atlanta, GA · On-site

$75 - $85/hr

... embedded software, networking, sensing, vision, AI, robotics, and field engineering. Key ... Responsibilities * Design and integrate complete systems spanning electrical, embedded, software ...

Deep, hands-on security engineering experience embedded in the software development lifecycle, from design and code review through CI/CD, deployment, and production. * Hands-on AI/LLM and agentic ...

Deep, hands-on security engineering experience embedded in the software development lifecycle, from design and code review through CI/CD, deployment, and production. * Hands-on AI/LLM and agentic ...

Deep, hands-on security engineering experience embedded in the software development lifecycle, from design and code review through CI/CD, deployment, and production. * Hands-on AI/LLM and agentic ...

Sr Advanced AI Platform Engineer

Atlanta, GA · On-site

$117K - $155K/yr

Experience with edge AI deployment on NVIDIA Jetson or similar embedded GPU platforms. * Experience with knowledge graphs, ontology engineering, or semantic web technologies. WE VALUE * Bachelor ...

... Engineer to work on a 6+ month contract position with potential for extension in Atlanta, GA ... Design and integrate systems spanning electrical, embedded, software, networking, sensing, AI, and ...

... Engineer to work on a 6+ month contract position with potential for extension in Atlanta, GA ... Design and integrate systems spanning electrical, embedded, software, networking, sensing, AI, and ...

Showing results 41-60

Embedded Ai Engineer information

See Atlanta, GA salary details

$67.3K

$147.5K

$167.3K

How much do embedded ai engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for embedded ai engineer in Atlanta, GA is $147,502.00, according to ZipRecruiter salary data. Most workers in this role earn between $126,500.00 and $166,400.00 per year, depending on experience, location, and employer.

What is an embedded AI engineer?

An Embedded AI Engineer is a professional who designs, develops, and implements artificial intelligence (AI) algorithms and models directly onto embedded systems, such as microcontrollers or edge devices. Their work involves optimizing AI solutions to run efficiently on hardware with limited computing resources, power, and memory. They collaborate with hardware engineers and software developers to integrate machine learning, computer vision, or other AI functionalities into products like smart appliances, autonomous vehicles, or IoT devices. Their expertise helps bring intelligent features directly to devices, enabling real-time decision-making without needing constant cloud connectivity.

What are the key skills and qualifications needed to thrive as an embedded AI engineer?

To thrive as an Embedded AI Engineer, you need expertise in embedded systems, AI/ML algorithms, programming languages like C/C++ and Python, and typically a degree in computer engineering or a related field. Familiarity with development tools such as TensorFlow Lite, ONNX, embedded Linux, and microcontroller platforms is essential, along with experience deploying AI models on resource-constrained devices. Strong problem-solving, collaboration, and communication skills help you work effectively in multidisciplinary teams and address real-world challenges. These skills ensure efficient integration of AI into embedded systems, enabling innovative, high-performance solutions for edge computing.

How does an embedded AI engineer typically collaborate with hardware and software teams during a project?

Embedded AI Engineers work closely with both hardware and software teams to ensure AI models are efficiently integrated into resource-constrained devices. They often collaborate with hardware engineers to optimize model performance based on device limitations like memory and processing power. At the same time, they coordinate with software developers to design efficient firmware and manage data pipelines. Regular cross-functional meetings and code reviews are common to address integration challenges and maintain alignment throughout the project lifecycle.

What is the difference between Embedded Ai Engineer vs Machine Learning Engineer?

CriteriaEmbedded Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's in Electrical Engineering, Computer Science, or related; knowledge of embedded systemsBachelor's or Master's in Computer Science, Data Science, or related; strong programming skills
Work EnvironmentEmbedded systems, IoT devices, hardware integrationData centers, cloud platforms, software development environments
Employer & Industry UsageConsumer electronics, automotive, IoT companiesTech firms, startups, research institutions
Common Search & ComparisonYesNo

Embedded Ai Engineers focus on integrating AI algorithms into embedded hardware and IoT devices, requiring knowledge of hardware constraints and embedded programming. Machine Learning Engineers develop models primarily for software applications and data analysis. While both roles involve AI, Embedded Ai Engineers specialize in hardware-software integration within embedded systems, whereas Machine Learning Engineers work on developing and deploying AI models in software environments.

What are popular job titles related to Embedded Ai Engineer jobs in Atlanta, GA?

For Embedded Ai Engineer jobs in Atlanta, GA, the most frequently searched job titles are:

What job categories do people searching Embedded Ai Engineer jobs in Atlanta, GA look for?

The top searched job categories for Embedded Ai Engineer jobs in Atlanta, GA are:

What cities near Atlanta, GA are hiring for Embedded Ai Engineer jobs?

Cities near Atlanta, GA with the most Embedded Ai Engineer job openings:

Infographic showing various Embedded Ai Engineer job openings in Atlanta, GA as of August 2026, with employment types broken down into 72% Full Time, and 28% Contract. Highlights an 45% In-person, and 55% Remote job distribution, with an average salary of $147,502 per year, or $70.9 per hour.

Director, Enterprise Artificial Intelligence (AI)

Interface, Inc.

Atlanta, GA • On-site

Full-time

Posted 25 days ago


Job description

Interface is a global flooring and sustainability leader dedicated to rethinking how spaces work for people and the planet. Our portfolio includes Interface® carpet tile and LVT, nora® rubber flooring, and FLOR® premium area rugs. Across every brand, we innovate in a way that combines design, performance, and sustainability-without compromise.
Trusted by architects, designers, and building professionals worldwide, we help bring bold visions to life with solutions that deliver real, measurable impact. Building on more than 30 years of sustainability progress and industry-first innovation, we remain 'all in' on our goal of becoming carbon negative by 2040, without the use of offsets.
The Director, Enterprise Artificial Intelligence (AI) is responsible for driving the execution of Interface's enterprise AI strategy-translating vision into scalable, secure, and value-generating solutions across commercial and corporate functions.
This role serves as the bridge between business leaders, technology teams, and strategic partners to identify, prioritize, and deliver AI use cases that improve decision-making, accelerate growth, and increase operational efficiency-while ensuring strong governance, security, and ethical use of AI.
The role will act as Interface's AI execution leader, owning delivery, adoption, and measurable outcomes, not experimentation in isolation.
Key Responsibilities:
AI Strategy Execution & Delivery
• Execute Interface's enterprise AI roadmap, aligned to company strategy, digital priorities, and value creation goals.
• Translate strategic AI priorities into clearly defined programs, use cases, and roadmaps with measurable business outcomes.
• Lead delivery of AI initiatives across domains and functions.
• Provides Project Management services for the key AI projects.
Use Case Identification & Business Partnership
• Partner with senior business leaders to identify, vet, and prioritize high-impact AI opportunities.
• Drive structured use case intake, value assessment, and sequencing to ensure focus on ROI-driven outcomes.
• Serve as a trusted advisor to business teams on where and how AI can responsibly accelerate results.
AI Architecture
• Define and lead the enterprise AI architecture strategy, establishing scalable, secure, and reusable AI platforms, services, and integration patterns
• Design and govern the enterprise AI ecosystem, including large language models (LLMs), AI agents, knowledge platforms, data foundations, vector databases, orchestration frameworks, APIs, and cloud AI services
• Architect enterprise data and knowledge foundations for AI, including data pipelines, metadata, semantic layers, retrieval-augmented generation (RAG), knowledge management, and data quality controls required to deliver trusted AI outcomes.
• Drive AI technology standards and solution architecture reviews, evaluating emerging AI capabilities, platforms, vendors, and reference architectures while ensuring interoperability, scalability, reliability, and operational excellence across the enterprise
Governance, Risk & Responsible AI
• Lead AI governance in partnership with Security, Legal, Privacy, and Compliance teams.
• Ensure AI solutions align with Interface standards for:
- Data privacy and security
- Ethical and responsible AI use
- Model transparency and explainability
• Establish guardrails, patterns, and standards for internal and vendor-provided AI solutions.
Technology & Partner Management
• Leverage strategic platforms and partners (e.g., Microsoft, Salesforce, Adobe, Workday, others) to accelerate AI adoption.
• Evaluate third-party AI tools and embedded AI capabilities with a "buy vs. build" mindset.
• Collaborate with Enterprise Architecture and Engineering teams to ensure scalability, interoperability, and long-term viability.
• Define and track adoption, usage, and value realization metrics.
Team Leadership & Operating Model
• Lead and mentor a small, high-impact AI delivery team (internal and/or hybrid with partners).
• Establish a lean operating model focused on rapid iteration, business outcomes, and continuous improvement.
• Influence without authority across global, matrixed teams.
Required Qualifications:
• Bachelor's degree in computer science, Engineering, Business, or related field; Master's preferred.
• 8-12+ years of experience across digital, analytics, AI, or advanced technology roles.
• Proven experience leading enterprise AI or advanced analytics initiatives from concept through production.
• Strong understanding of:
- Applied AI / machine learning concepts (not pure research)
- Data platforms, cloud ecosystems, and modern enterprise architectures
- AI risks related to privacy, security, bias, and compliance
• Demonstrated ability to partner with senior business leaders and influence outcomes.
• Experience operating in a global, matrixed organization.
Preferred Experience:
• Experience deploying AI solutions leveraging hyperscale's (e.g., Microsoft Azure AI / Google Cloud)
• Background in manufacturing, industrial, supply chain, or commercial B2B environments.
• Exposure to embedded AI within enterprise platforms (CRM, ERP, productivity tools).
• Experience establishing AI governance frameworks or centers of enablement
4 - Mid-Senior Level / Management
Learn more about Interface (NASDAQ: TILE) and our brands at interface.com and FLOR.com. Join us on Facebook, Instagram, LinkedIn, and Pinterest.
We are a VEVRAA Federal Contractor. We desire priority referrals of Protected Veterans for job openings at all locations within the State of Georgia. An Equal Opportunity Employer including Veterans and Disabled.