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Google Cloud Machine Learning Engineer Jobs in Augusta, GA

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 ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

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 ...

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Google Cloud Machine Learning Engineer information

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

As of Jul 29, 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 are Google Cloud Machine Learning Engineers?

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, and why are they important?

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 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 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 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:
What are popular job titles related to Google Cloud Machine Learning Engineer jobs in Augusta, GA? For Google Cloud Machine Learning Engineer jobs in Augusta, GA, the most frequently searched job titles are:
What cities near Augusta, GA are hiring for Google Cloud Machine Learning Engineer jobs? Cities near Augusta, GA with the most Google Cloud Machine Learning Engineer job openings:

Machine Learning Engineer

Ksb

Grovetown, GA

Other

Posted 22 days 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.