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Google Cloud Machine Learning Engineer Jobs in Georgia

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

$120 - $165/hr

Google Gemini (multimodal reasoning, advanced RAG integration). * Meta LLaMA (fine‑tuned/custom ... Leverage cloud ML platforms (AWS SageMaker, Databricks ML) for experimentation and scaling.

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

Google Gemini (multimodal reasoning, advanced RAG integration). * Meta LLaMA (fine-tuned/custom ... Leverage cloud ML platforms (AWS Sagemaker, Databricks ML) for experimentation and scaling.

Equifax, Inc.

Machine Learning Engineer

Atlanta, GA · On-site

Equifax is excited to add a Machine Learning Engineer to our team. What you'll do * Design complex ... Cloud Certification Strongly Preferred What could set you apart * Application Development ...

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 ...

Google

Platform Customer Engineer, Google Cloud

Atlanta, GA · On-site

$53.50 - $71.75/hr

About the job As a Platform Customer Engineer (CE), you will partner with technical Sales teams to differentiate Google Cloud to our customers. You will serve as the customer's primary technical ...

FanDuel

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

As a Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast ... Experience working in a cloud environment such as AWS, Google Cloud Platform, Azure. * Experience ...

Waystar, Inc

Senior ML Engineer

Atlanta, GA · On-site

$100 - $160/hr

... and innovative Machine Learning Engineer to develop end‑to‑end ML pipelines, fine‑tune language models, design agentic architectures, and deploy solutions on Google Cloud Platform.

Winixx

Machine Learning Engineer

Atlanta, GA · On-site

$130 - $185/hr

Openings › Software › Machine Learning Engineer Software Machine Learning Engineer Atlanta, US Remote Full-time $130,000 - $185,000 About Winixx Winixx Inc. is a New York-based technology holding ...

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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 Aug 8, 2026, the average hourly pay for google cloud machine learning engineer in Georgia is $53.10, according to ZipRecruiter salary data. Most workers in this role earn between $45.24 and $60.48 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 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 Georgia? The most popular types of Google Cloud Machine Learning Engineer jobs in Georgia are:
What are popular job titles related to Google Cloud Machine Learning Engineer jobs in Georgia? For Google Cloud Machine Learning Engineer jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Google Cloud Machine Learning Engineer jobs in Georgia look for? The top searched job categories for Google Cloud Machine Learning Engineer jobs in Georgia are:
What cities in Georgia are hiring for Google Cloud Machine Learning Engineer jobs? Cities in Georgia with the most Google Cloud Machine Learning Engineer job openings:
Google Cloud Machine Learning Engineer jobs near you

Machine Learning Engineer III 4P/791

4P Consulting Inc.

Atlanta, GA

Contractor

Posted 7 days ago

Job description

Position: Machine Learning Engineer III – AI/ML Product Engineering

Location: Atlanta, GA

Duration: 5 Months
Client: Southern Company Services

Southern Company Services is seeking an experienced Machine Learning Engineer III to develop scalable, reusable, and production-grade AI products for deployment across multiple operating companies.

This role will focus on Retrieval-Augmented Generation, multi-agent systems, natural language processing, model deployment, and cloud-based AI solutions. The ideal candidate will have strong software engineering skills, hands-on AI/ML experience, and expertise with Azure or Google Cloud Platform.

Key Responsibilities

· Design and build modular, reusable AI components and services.

· Develop scalable RAG solutions using structured and unstructured data.

· Engineer multi-agent systems for task coordination, workflow automation, and decision support.

· Build transcription and NLP pipelines for customer-interaction analysis.

· Develop and fine-tune models using PyTorch, Hugging Face Transformers, LangChain, or similar frameworks.

· Package and deploy models using Azure Machine Learning, Google Cloud Platform, or Databricks.

· Integrate Databricks for data ingestion, feature engineering, experimentation, and model development.

· Develop reusable libraries, APIs, templates, and engineering patterns.

· Partner with MLOps, DevOps, data engineering, architecture, and product teams.

· Implement monitoring for model performance, data drift, system usage, and operational reliability.

· Ensure AI solutions meet enterprise security, privacy, compliance, scalability, and observability requirements.

· Provide technical guidance to teams adopting shared AI products and components.

Required Qualifications

· Strong experience developing and deploying production-grade AI and machine learning solutions.

· Hands-on experience with RAG architectures, LLM applications, multi-agent systems, and NLP.

· Experience with Azure AI services, Google Cloud Platform AI services, or Azure Machine Learning.

· Proficiency with Python and frameworks such as PyTorch, Transformers, or LangChain.

· Experience deploying scalable models and AI services in cloud environments.

· Knowledge of APIs, software engineering practices, model monitoring, and MLOps.

· Experience working with structured and unstructured datasets.

· Strong communication, collaboration, analytical, and problem-solving skills.

Preferred Qualifications

· Experience with Databricks, vector databases, embeddings, and semantic search.

· Experience building reusable enterprise AI platforms or shared AI services.

· Knowledge of model evaluation, data drift, observability, and responsible AI.

· Familiarity with CI/CD, containers, Kubernetes, and cloud-native deployment.

· Utility, energy, or regulated-industry experience is preferred.