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Google Cloud Machine Learning Engineer Jobs in Augusta, GA

KSB GIW, Inc.

Machine Learning Engineer

Grovetown, GA · On-site

$70 - $110/hr

Machine Learning Engineer Department: Engineering, Research & Development Reports to: Metallurgical ... Cloud compute (AWS or Azure) and GPU‑based training * Coursework or research projects in ...

New

KSB, Inc.

Machine Learning Engineer

Grovetown, GA · On-site

$70 - $95/hr

Machine Learning Engineer**### **KSB GIW, Inc.**### **Department:** Engineering, Research ... Cloud compute (AWS or Azure) and GPU-based training* Coursework or research projects in numerical ...

Ksb

Machine Learning Engineer

Grovetown, GA · On-site

Machine Learning Engineer KSB GIW, Inc. Department: Engineering, Research & Development Reports to ... Cloud compute (AWS or Azure) and GPU-based training * Coursework or research projects in numerical ...

Athena Technology Group, Inc. (ATG)

ATG is an Equal Opportunity/Affirmative Action Employer Minorities/Females/Vets/Disability Job Summary We are seeking a Data Scientist / Machine Learning Engineer to support advanced analytics and ...

Google

Data Center Mechanical Engineer

Appling, GA · On-site

Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We ... Conduct engineering analysis and research designs and methods of data center equipment and ...

Google

Data Center Electrical Engineer

Appling, GA · On-site

Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We ... Conduct engineering analysis and research designs and methods of data center equipment and ...

Varsity Tutors

Machine Learning Tutor

Augusta, GA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Textron

AI Engineer

Augusta, GA

Years of Experience: 5 years of experience in software engineering, AI engineering, machine learning engineering, cloud application development, or related technical work. Experience independently ...

New

Textron

AI Engineer

Augusta, GA

Years of Experience: 5 years of experience in software engineering, AI engineering, machine learning engineering, cloud application development, or related technical work. Experience independently ...

New

Textron

AI Engineer

Augusta, GA · On-site

Years of Experience: 5+ years of experience in software engineering, AI engineering, machine learning engineering, cloud application development, or related technical work. Experience independently ...

New

Google

Data Center Services Campus Lead

Appling, GA · On-site

$152K/yr

Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We ... that enable developers to build the future. From software to hardware our teams are shaping the ...

Google

Data Center Operations Facilities Manager

Appling, GA · On-site

$152K/yr

Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide. We ... that enable developers to build the future. From software to hardware our teams are shaping the ...

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All JobsGoogle Cloud Machine Learning Engineer JobsGoogle Cloud Machine Learning Engineer Jobs in Augusta, GA

Google Cloud Machine Learning Engineer information

See Augusta, GA salary details

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$59

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How much do google cloud machine learning engineer jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for google cloud machine learning engineer in Augusta, GA is $59.11, according to ZipRecruiter salary data. Most workers in this role earn between $50.38 and $67.36 per hour, depending on experience, location, and employer.

What is a Google Cloud Machine Learning engineer?

Google Cloud Machine Learning Engineers are professionals who design, build, and deploy machine learning models using Google Cloud Platform (GCP) services and tools. They work with large datasets, develop scalable ML solutions, and collaborate with data scientists and software engineers. Their role often includes automating data pipelines, optimizing model performance, and ensuring the reliability and security of ML deployments on the cloud. These engineers have expertise in both machine learning algorithms and cloud infrastructure, making them key contributors to data-driven projects.

What are the key skills and qualifications needed to thrive as a Google Cloud Machine Learning engineer?

To thrive as a Google Cloud Machine Learning Engineer, you need strong programming skills in Python or Java, a deep understanding of machine learning algorithms, and a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, TensorFlow, and relevant certifications like the Professional Machine Learning Engineer certification is highly valuable. Excellent problem-solving abilities, collaboration, and clear communication make someone stand out in this position. These skills and qualities are critical for designing, deploying, and optimizing scalable ML solutions that meet business objectives in cloud environments.

What are some typical cross-functional collaborations for a Google Cloud Machine Learning engineer?

As a Google Cloud Machine Learning Engineer, you'll frequently work alongside data scientists, software engineers, and product managers to design, deploy, and maintain machine learning solutions at scale. Collaboration often involves translating business requirements into machine learning pipelines, integrating models into cloud-based applications, and ensuring that solutions are robust, secure, and scalable. Regular communication with DevOps and infrastructure teams is also common to optimize model deployment and monitor performance. This cross-disciplinary teamwork is crucial for delivering impactful, production-ready AI solutions.

What is the difference between Google Cloud Machine Learning Engineer vs Data Scientist?

AspectGoogle Cloud Machine Learning EngineerData Scientist
Required CredentialsGoogle Cloud certifications, programming skills, ML knowledgeStatistics, data analysis, programming, often with advanced degrees
Work EnvironmentCloud platforms, coding, deploying ML modelsData analysis, modeling, reporting, often in research or business settings
Employer & Industry UsageTech companies, cloud service providers, enterprises using Google CloudVarious industries including finance, healthcare, marketing, research

Google Cloud Machine Learning Engineers focus on developing and deploying ML models on Google Cloud, requiring cloud certifications and coding skills. Data Scientists analyze data, build models, and generate insights, often with advanced degrees. While both roles work with data and ML, the Engineer role emphasizes cloud deployment and infrastructure, whereas Data Scientists focus on data analysis and modeling.

What are the most commonly searched types of Google Cloud Machine Learning Engineer jobs in Augusta, GA?

The most popular types of Google Cloud Machine Learning Engineer jobs in Augusta, GA are:

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For Google Cloud Machine Learning Engineer jobs in Augusta, GA, the most frequently searched job titles are:

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Cities near Augusta, GA with the most Google Cloud Machine Learning Engineer job openings:

Google Cloud Machine Learning Engineer jobs near you

Machine Learning Engineer

KSB GIW, Inc.

Grovetown, GA • On-site

$70 - $110/hr

Other

Posted 3 days ago

New

Job description

Machine Learning Engineer

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:
    • 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
    • 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.

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