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Embedded Machine Learning Engineer Jobs in Georgia

TheTalentos, LLC

Machine Learning Engineer

Atlanta, GA · On-site

Machine Learning Engineer Atlanta, Georgia, United States About the Job We are supporting a client in the Risk and Insurance industry in the search for a driven Machine Learning Engineer to help us ...

Keylent Inc

Machine Learning Engineer

Atlanta, GA · On-site

$110.10K - $132.20K/yr

Machine Learning Engineer TECHM-JOB-30814 Position :- Machine Learning Engineer Location :- Atlanta GA (Day 1 onsite) Preferably 10+ years' experience having strong Data Analytical Skills with Hands ...

Indeed

Machine Learning Engineer

Atlanta, GA · On-site

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

CNN

Machine Learning Engineer I

Atlanta, GA · On-site

CNN is a global leader in news and information, seeking a Machine Learning Engineer I to build and deploy ML systems that enhance personalization, search, recommendations, and content understanding ...

Indeed

Machine Learning Engineer III

Atlanta, GA · On-site

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

Indeed

Staff Machine Learning Engineer

Atlanta, GA · On-site

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III you will be a team lead on the Marketplace Efficiency - Job Reach team. Your team will be responsible for maintaining ...

AppFolio

Sr. Machine Learning Engineer

GA · Remote

$100.50K - $138K/yr

Assistant: a GenAI copilot embedded across the product experience * Flows: an agentic workflow ... Who we are looking for We're seeking a Sr Machine Learning Engineer to play a critical role in ...

AppFolio

Sr. Machine Learning Engineer

Atlanta, GA · Remote

$100.50K - $138K/yr

Assistant : a GenAI copilot embedded across the product experience * Flows: an agentic workflow ... Who we are looking for We're seeking a Sr Machine Learning Engineer to play a critical role in ...

Omnissa

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$162.51K - $342.75K/yr

Staff Machine Learning Engineer We are Omnissa. The world is evolving quickly, and organizations everywhere--from global enterprises to educational institutions--are under pressure to deliver ...

Omnissa

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$162.51K - $342.75K/yr

As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems that power predictive analytics, personalization, automation, and intelligent platform behaviors.You ...

Saxon Global

Machine Learning Engineer

Atlanta, GA · On-site

We're partnering with a client to hire ML Search Engineers who are excited about building a modern, machine learning-driven search platform that powers intelligent product discovery across a large e ...

Hire Talent

Lead Machine Learning Engineer

Atlanta, GA · On-site

$98.60K - $129.80K/yr

Lead Machine Learning Engineer Location: Atlanta, GA Duration: 5 Months Duties: In new product design roles: develops and programs integrated software algorithms to structure, analyze and leverage ...

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All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Georgia

Embedded Machine Learning Engineer information

See Georgia salary details

$59.1K

$129.5K

$146.9K

How much do embedded machine learning engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for embedded machine learning engineer in Georgia is $129,514.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $146,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Embedded Machine Learning Engineer, and why are they important?

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by Embedded Machine Learning Engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What does an Embedded Machine Learning Engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

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

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Georgia? For Embedded Machine Learning Engineer jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning Engineer jobs in Georgia look for? The top searched job categories for Embedded Machine Learning Engineer jobs in Georgia are:
What cities in Georgia are hiring for Embedded Machine Learning Engineer jobs? Cities in Georgia with the most Embedded Machine Learning Engineer job openings:
Embedded Machine Learning Engineer jobs near you
Infographic showing various Embedded Machine Learning Engineer job openings in Georgia as of May 2026, with employment types broken down into 96% Full Time, 2% Part Time, and 2% Contract. Highlights an 92% Physical, and 8% Remote job distribution, with an average salary of $129,514 per year, or $62.3 per hour.

Machine Learning Engineer

TheTalentos, LLC

Atlanta, GA • On-site

Other

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

Job description

Machine Learning Engineer

Atlanta, Georgia, United States

About the Job

We are supporting a client in the Risk and Insurance industry in the search for a driven Machine Learning Engineer to help us bring software development rigor to the ML life-cycle within the business insurance industry. As an experienced innovator partnering with the marketing and growth teams, this is a massive opportunity to drive high growth impact at a hyper-growth startup. Your job is to be a full-stack ML engineer, supercharging all aspects of scaling Machine Learning at NEXT: application design and architecture, scalable deployment of inference solutions as APIs, data enrichment as a service, and model monitoring.

You will be joining an innovative division of based in Atlanta: Data Labs. The mandate of Data Labs is to build software and data solutions that meaningfully impact marketing, funnel, risk, and servicing/claims experiences.

What You'll Do:

  • Empower our team of data scientists to rapidly develop and deploy ML solutions.
  • Leverage software engineering best practices to create and deploy data-intensive and machine learning inference products.
  • Understand the data and dig deep to extract actionable insights.
  • Think creatively and outside the box to answer desired experimental questions as well as expose opportunities to create business value.
  • Work cross-functionally with marketing, engineering, product, senior management, and external partners.

What We Need:

  • 3+ years of hands-on experience in the complete software development life-cycle with demonstrated professional experience with machine learning
  • Strong command of Python and the standard web development frameworks (e.g. Django, Flask, FastAPI) & fluency with database technologies, SQL, and Python data packages
  • Demonstrated experience deploying models and applications to a cloud environment using tools like Docker and Kubernetes.
  • Demonstrated experience with software engineering best practices, such as Test-Driven Development and continuous integration/deployment pipeline
  • Experience with ML-oriented data pipelining tools (dbt, Airflow, Prefect, DVC, etc.)

Unstoppable Qualities:

  • Experience in the insurance industry (strong fintech/lending experience will also be considered)
  • Experience with GitLab

Relocation assistance: Limited assistance

Apply