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Google Cloud Machine Learning Engineer Jobs in Raleigh, NC

ExtendMyTeam

Machine Learning Engineer

Cary, NC

This is a hands-on engineering role focused on production systems, model deployment, APIs ... Exposure to cloud platforms such as AWS, GCP, or Azure * Understanding of taking machine learning ...

Telus Digital

Google CX Engineer

Durham, NC · On-site +1

Active Google Cloud Professional Certifications such as Professional Cloud Architect, Professional Machine Learning Engineer, or Professional Data Engineer. * Practical expertise with Google Customer ...

Q2 Software, Inc.

Machine Learning Engineer

Cary, NC · On-site

As a Machine Learning Engineer, you will help build and operate production systems that power our ... Familiarity with cloud platforms (AWS, GCP, or Azure). * Exposure to MLOps concepts such as CI/CD ...

Q2

Machine Learning Engineer

Cary, NC · On-site

As a Machine Learning Engineer, you will help build and operate production systems that power our ... Familiarity with cloud platforms (AWS, GCP, or Azure). * Exposure to MLOps concepts such as CI/CD ...

CoVar

Machine Learning Engineer

Durham, NC

Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC, that uses artificial intelligence to solve problems that matter. We develop AI/ML tools to help the ...

Vadum, Inc.

Machine Learning Engineer

Raleigh, NC · On-site

$96K - $137K/yr

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

Vadum Inc

Machine Learning Engineer

Raleigh, NC · On-site

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

Vadum Inc

Machine Learning Engineer

Raleigh, NC

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

Deloitte

AI Solutions Leader

Raleigh, NC · On-site

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

OptiTrack

Machine Learning & Operations Engineer

Durham, NC · Remote

$71.10K - $96.20K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale ... Optimize GPU/compute utilization across cloud and on-prem environments. * Deploy, monitor, and ...

OptiTrack

Machine Learning & Operations Engineer

Durham, NC · Remote

$67.20K - $90.80K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale ... Optimize GPU/compute utilization across cloud and on-prem environments. * Deploy, monitor, and ...

Google

Software Engineer AI/ML Networking

Raleigh, NC · On-site

Experience with Machine Learning Infrastructure. About the job Google's software engineers develop ... Google Cloud accelerates every organization's ability to digitally transform its business and ...

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Google Cloud Machine Learning Engineer information

See Raleigh, NC salary details

$22

$61

$84

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

As of May 29, 2026, the average hourly pay for google cloud machine learning engineer in Raleigh, NC is $61.13, according to ZipRecruiter salary data. Most workers in this role earn between $52.12 and $69.62 per hour, depending on experience, location, and employer.

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 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 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 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 popular job titles related to Google Cloud Machine Learning Engineer jobs in Raleigh, NC? For Google Cloud Machine Learning Engineer jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Google Cloud Machine Learning Engineer jobs in Raleigh, NC look for? The top searched job categories for Google Cloud Machine Learning Engineer jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Google Cloud Machine Learning Engineer jobs? Cities near Raleigh, NC with the most Google Cloud Machine Learning Engineer job openings:
Google Cloud Machine Learning Engineer jobs near you

Machine Learning Engineer

ExtendMyTeam

Cary, NC

Full-time

Posted 10 days ago

Job description

Join a high-growth financial technology organization focused on building modern digital banking, payments, lending, and risk solutions for financial institutions and fintech partners. This team is investing in machine learning and analytics capabilities to help improve fraud detection, predictive insights, and operational decision-making across customer-facing products.

This is an opportunity to work on applied machine learning systems that directly support real-world fraud and risk workflows. The team owns solutions end-to-end and is focused on building scalable, production-ready ML applications that deliver measurable customer impact.

Position Summary

We are seeking a Machine Learning Engineer to help design, deploy, and support production machine learning systems within a collaborative engineering organization. This individual will work closely with software engineers, data scientists, and product teams to operationalize machine learning models, improve ML infrastructure, and support scalable analytics workflows.

This is a hands-on engineering role focused on production systems, model deployment, APIs, pipelines, and ML operations rather than purely research-oriented machine learning work.

Responsibilities

  • Build and maintain systems and pipelines supporting machine learning training, evaluation, inference, and monitoring

  • Deploy and support machine learning models in production environments

  • Write clean, scalable, maintainable, and well-tested Python code

  • Support monitoring, troubleshooting, and optimization of production ML systems and data pipelines

  • Collaborate cross-functionally with engineering, data science, and product teams to operationalize ML solutions

  • Improve the reliability, scalability, and performance of ML infrastructure and services

  • Contribute to tooling and processes that support the machine learning development lifecycle

  • Participate in code reviews, technical discussions, and collaborative problem solving

Required Qualifications

  • 2+ years of experience in machine learning engineering, software engineering, or related technical experience

  • Strong Python development experience

  • Experience working with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn

  • Experience deploying or supporting machine learning models in production environments

  • Experience writing clean, maintainable code and using version control tools such as Git

  • Exposure to cloud platforms such as AWS, GCP, or Azure

  • Understanding of taking machine learning models from research/development into production systems

Additional Information

  • Hybrid work environment based in Cary, NC

  • Applicants must be authorized to work in the U.S. without sponsorship

  • Competitive compensation, benefits, flexible time off, and career development opportunities