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Artificial Intelligence Machine Learning Engineer Jobs in Georgia

Machine Learning Engineer KSB GIW, Inc. Department: Engineering, Research & Development Reports to: Metallurgical and Materials R&D Lab Manager Location: Grovetown, GA, USA (onsite) Shift: First FLSA ...

Machine Learning Engineer Employment Type: Full Time Location: Atlanta, GA Description We are seeking a skilled and forward-looking ML Engineer with experience in Large Language Models (LLMs ...

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 ...

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Machine Learning Engineer

Atlanta, GA · On-site

$50 - $60/hr

Machine Learning Engineer 3 Date Posted: 7/31/26 Location: Atlanta, GA 30308 Job Type: Contract Full-Time Immediate W2 contract position available in Atlanta, GA. Estimated Duration: 4.5 months ...

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Within the Data & Audience Platform (DAP) organization, our Machine Learning Engineering team builds the foundational AI/ML intelligence that powers identity, audience, advertising, and ...

Senior Machine Learning Engineer

Atlanta, GA

$100K - $138K/yr

Within the Data & Audience Platform (DAP) organization, our Machine Learning Engineering team builds the foundational AI/ML intelligence that powers identity, audience, advertising, and ...

Agentic AI Engineer We are seeking a highly skilled Agentic AI Engineer to support advanced R&D ... Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$162K - $342K/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 ...

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Artificial Intelligence Machine Learning Engineer information

See Georgia salary details

$26.6K

$108.7K

$163.4K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for artificial intelligence machine learning engineer in Georgia is $108,730.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,700.00 and $130,900.00 per year, depending on experience, location, and employer.

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by artificial intelligence machine learning engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What is the difference between Artificial Intelligence Machine Learning Engineer vs Data Scientist?

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.
What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Georgia? For Artificial Intelligence Machine Learning Engineer jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Georgia look for? The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Georgia are:
What cities in Georgia are hiring for Artificial Intelligence Machine Learning Engineer jobs? Cities in Georgia with the most Artificial Intelligence Machine Learning Engineer job openings:
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $108,730 per year, or $52.3 per hour.

Machine Learning Engineer

Ksb

Grovetown, GA

Other

Re-posted 23 hours ago


Job description

KSB is a leading supplier of pumps, valves and related service. Our reliable, high-efficiency products are used in applications wherever fluids need to be transported or shut off, covering everything from building services,industry and water transport to waste water treatment, power plant processes and mining. Founded in 1871 in Frankenthal, Germany, the company has a presence on all continents with its own sales and marketing organisations and manufacturing facilities. Around the globe, more than 190 service centres and around 3,500 service specialists are on hand to provide local inspection, servicing, maintenance and repair services under the KSB SupremeServ brand. Innovative technology that is the fruit of KSB's research and development activities forms the basis for the company's success.
People. Passion. Performance. It is these three success factors that make KSB the company it is today.
At KSB, we recognise that it is people who actually make the difference - the people we employ and the people we serve. This is why we are committed to equal rights and treatment worldwide and never lose sight of the aspects ecology and sustainability when manufacturing our products.

Machine Learning Engineer KSB GIW, Inc.

Department: Engineering, Research & Development
Reports to: Metallurgical and Materials R&D Lab Manager
Location: Grovetown, GA, USA (onsite)
Shift: First

FLSA Status: Salary Exempt

OVERVIEW:

Our R&D group is expanding its use of machine learning to solve real engineering problems, and we're looking for a sharp, hands-on early-career engineer to join the team.

You'll work at the intersection of machine learning and the physical world to build AI systems that learn from real industrial data and connect with the engineering models behind them. The role lives where machine learning meets scientific computing: surrogate modeling, data-driven approximations of physical systems, and ML models that respect the underlying engineering principles.

You'll build the data foundation that powers this work, implement and train models that bridge physics-based simulation with modern machine learning, and work closely with an experienced technical lead who will guide your growth across data engineering, scientific ML, and emerging AI tooling.

RESPONSIBILITIES:

  • Build and maintain the data foundation: ingestion, cleaning, transformation, validation, and metadata standards
  • Implement and train machine learning models using Python and modern frameworks (PyTorch)
  • Contribute to applied AI tooling that supports the broader R&D workflow
  • Develop visualization and dashboard interfaces that present results to end users
  • Run experiments, track results, and report findings against defined targets
  • Help bring prototype code to production quality: testing, documentation, version control
  • Collaborate with team members across engineering disciplines

QUALIFICATIONS:

  • Education:Bachelor's degree required; master's preferred in Computer Science, Engineering, Applied Math, Physics, or a related field
  • Experience:1-3 years of professional or substantial project experience in machine learning, data engineering, or scientific computing

SKILLS / COMPETENCIES

Required:
  • Solid Python skills with hands-on experience using core libraries:
    • Machine learning: PyTorch, scikit-learn
    • Data: NumPy, pandas
    • Scientific computing: SciPy, Matplotlib
  • Foundational understanding of scientific computing: numerical methods, simulation concepts, or modeling of physical systems - this is essential to the role
  • Foundational understanding of neural networks, model training, and optimization
  • Experience with version control (Git) and working in a Linux environment
  • Strong written and verbal communication skills
  • Collaborative, coachable attitude
Preferred:
  • Experience building and maintaining data pipelines, metadata schemas, and data quality frameworks
  • Exposure to scientific / physics-informed machine learning (surrogate modeling, embedding physical constraints into ML models)
  • Background in CFD, simulation, computational mechanics, or applied physics
  • Familiarity with agentic AI / LLM frameworks (LangChain, LangGraph, or similar) enough to collaborate effectively, not lead
  • Experience with Jupyter, Docker, MLflow, or FastAPI
  • Front-end / dashboard development experience (React)
  • Cloud compute (AWS or Azure) and GPU-based training
  • Coursework or research projects in numerical methods, engineering, or applied science

PHYSICAL REQUIREMENTS:

  • Primarily desk-type duty

KSB Group is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.

This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. KSB makes hiring decisions based solely on qualifications, merit, and business needs at the time.

We value employees who take the initiative and are committed to our company; Employees who take responsibility and for whom business success is the focus of their actions. In return, we offer fair framework conditions for collective wages and pensions, flexible working time models, individual training opportunities and the best career prospects.