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Google Cloud Machine Learning Engineer Jobs in Georgia

PrizePicks

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize ... Cloud Native: Deep experience with GCP services (BigQuery, Cloud Functions, GKE, Vertex AI) or AWS ...

The E Group

Be Seen First

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 ...

Bespoke Labs

Machine Learning Engineer

Kennesaw, GA

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 ...

Bespoke Labs

Machine Learning Engineer

Savannah, GA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Columbus, GA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Valdosta, GA

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 ...

Bespoke Labs

Machine Learning Engineer

Valdosta, GA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Savannah, GA

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 ...

Bespoke Labs

Machine Learning Engineer

Macon, GA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Atlanta, GA

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 ...

Bespoke Labs

Machine Learning Engineer

Athens, GA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Carrollton, GA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Kennesaw, GA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Macon, GA

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 ...

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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:
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Google Cloud Machine Learning Engineer jobs near you

Staff Machine Learning Engineer

PrizePicks

Atlanta, GA • On-site, Remote

$220K - $280K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 2 days ago

Job description

At PrizePicks, we are the fastest-growing sports company in North America, as recognized by Inc. 5000. As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues, including the NFL, NBA, and Esports titles like League of Legends and Counter-Strike. Our team of over 550 employees thrives in an inclusive culture that values individuals from diverse backgrounds, regardless of their level of sports fandom. Ready to reimagine the DFS industry together?
As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet, Deposit Velocity, and Platform Integrity by integrating robust, low-latency ML models across our sports betting and daily fantasy ecosystems.
What you'll do:
  • Architect Scalable ML Systems: Design and build the end-to-end machine learning infrastructure, transitioning experimental Data Science models into robust, high-availability production services.
  • Real-Time Inference at Scale: Steer the design and deployment of low-latency services to serve model inferences in milliseconds. You will power real-time decisions across the platform, from dynamic oddsmaking and risk analysis to smart deposit defaults.
  • Feature Engineering & Data Strategy: Partner with Data Science to build scalable logging and data pipelines. You will lead the creation and optimization of a centralized feature store required to train complex models across diverse business domains.
  • End-to-End MLOps Leadership: Champion best practices for model deployment, monitoring, and CI/CD for ML. You will implement automated retraining pipelines and observability tools to ensure data drift and model degradation are caught and addressed instantly.
What you have:
  • 7+ years of experience in Machine Learning Engineering or Backend Engineering, with a proven track record of deploying and maintaining complex ML models in high-traffic production environments.
  • 3+ years of technical leadership, acting as a lead and driving architecture decisions for consumer applications or scalable backend platforms.
  • Experience with Real-Time Data: Proficient in streaming architectures (Kafka/Flink/PubSub) and building low-latency services to serve model inference in <100ms.
  • MLOps Expertise: Deep experience managing the full ML lifecycle (training, deploying, monitoring) using tools like MLFlow, Kubeflow, Databricks, or SageMaker.
  • Strong Coding Skills: Expert in Python and SQL; proficiency in Go, C++, or Rust is a strong plus for building high-performance inference layers.
  • Cloud Native: Deep experience with GCP services (BigQuery, Cloud Functions, GKE, Vertex AI) or AWS equivalents.
What makes you stand out:
  • Experience implementing reinforcement learning or complex probabilistic models for dynamic pricing, risk management, or fraud detection.
  • Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading.
  • Experience building and scaling "Feature Stores" that successfully bridge batch historical data with real-time event streams.
Where you'll live:
  • While we prefer candidates based in Atlanta, we are open to qualified applicants from anywhere in the U.S. and are willing to consider remote candidates. #LI-Remote
Working at PrizePicks:
The typical salary range for this position is $220,000 to $280,000. At PrizePicks, we consider your role, level, and where you'll be working when determining our salary ranges. The compensation info you see on our job postings gives you an idea of the starting pay range for the position. Your actual pay within that range will depend on your specific work location, as well as your skills, experience, and education. Your recruiter will be happy to chat more about the specific pay range for your location and how we arrived at it during the hiring process.
This application period will remain open for 30 days. We're committed to finding the best candidate, so this date may be adjusted, and any changes will be reflected in this posting.
Date Posted: 4/16/2026
1st Extension: 5/16/2026
2nd Extension: 6/16/2026
Benefits you'll receive:
In addition to your great compensation package, full-time employees will be eligible for the following perks:
  • Company-subsidized medical, dental, & vision plans
  • 401(k) plan with company match
  • Annual bonus
  • Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!)
  • Generous paid leave programs, including 16-week paid parental leave and disability benefits
  • Workplace flexibility and modern work schedules focused on getting the job done, not hours clocked
  • Company-wide in-person events and team outings
  • Lifestyle enhancement program
  • Company equipment provided (Windows & Mac options)
  • Annual performance reviews with opportunities for growth and career development

You must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
PrizePicks is an Equal Opportunity Employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

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