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Google Cloud Machine Learning Engineer Jobs in Raleigh, NC

LexisNexis

Principal Machine Learning Engineer I

Raleigh, NC · On-site

$136.10K - $252.80K/yr

We are seeking a Principal Machine Learning Engineer to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products.

Apple

AIML - Staff Machine Learning Engineer

Cary, NC

$212K - $386.30K/yr

Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more.

Apple

AIML - Staff Machine Learning Engineer

Cary, NC

$212K - $386.30K/yr

Building this system requires deep expertise in a myriad of cutting edge fields: search, natural language understanding, data engineering, machine learning, privacy preserving system design, and more.

Qualcomm

Machine Learning Compiler

Raleigh, NC · On-site

$160.60K - $240.80K/yr

Lead a team of engineers focused on advancing machine learning compiler technologies for cutting-edge AI accelerators for the Cloud and Datacenter market. This role combines deep technical expertise ...

Deloitte

AI Data Engineer Senior Consultant

Raleigh, NC · On-site

$111.30K - $133.70K/yr

... field • Cloud or artificial intelligence or machine learning certification • 4+ years of ... Google Cloud Platform for data platforms and scalable compute • 4+ years of experience ...

Deloitte

Databricks Engineer

Raleigh, NC · On-site +1

Experience with Databricks workspace administration, machine learning operations (MLOps), or ... Google Cloud Platform, including integrations * Develop and maintain Databricks notebooks, jobs ...

Pwc

Google Cloud Architect - Senior Manager

Raleigh, NC · On-site

$124K - $280K/yr

Cloud Digital Leader (Foundational), Generative AI Leader (Foundational), Cloud Engineer Associate, Cloud Developer Professional, Cloud Architect Professional, Machine Learning Engineer Professional ...

Wells Fargo

Lead Infrastructure Engineer

Raleigh, NC · On-site

$104.50K - $137.10K/yr

Build and enable Cloud infrastructure, automate the orchestration for Google Cloud Platforms (GCP ... Azure AI Foundry, Azure Machine Learning, Document Intelligence, Azure AI Search, Vertex AI ...

Qualcomm

Machine Learning Compiler

Raleigh, NC · On-site

... the Cloud and Datacenter market. The role involves leading a team to innovate ML compiler ... Required : • Bachelor's degree in Computer Science, Electrical Engineering, or related field and ...

Varsity Tutors

Machine Learning Tutor

Chapel Hill, NC · Remote

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

As of May 30, 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

Principal Machine Learning Engineer I

LexisNexis

Raleigh, NC • On-site

$136.10K - $252.80K/yr

Full-time

Posted 19 days ago

LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

147th of 424 rated business services

Job description

About our Team
LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (www.relx.com), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today's top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles (https://stories.relx.com/responsible-ai-principles/index.html).
About the Role
Do you love collaborating with teams to solve complex technical problems?
We are seeking a Principal Machine Learning Engineer to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This role combines deep ML expertise with distributed systems engineering and AI platform development.
You will play a key role in developing enterprise-grade AI systems, including large language model (LLM) infrastructure, retrieval-augmented generation (RAG) pipelines, and autonomous agent frameworks designed for complex large unstructured data.
Responsibilities:
  • Provide architectural direction and code-level guidance.
  • Establish engineering best practices for ML system design, testing, and deployment.
  • Conduct design reviews, performance reviews, and technical roadmap planning.
  • Architect distributed ML systems serving multiple global products.
  • Standardize infrastructure patterns for LLM serving and retrieval systems.
  • Define and implement enterprise-ready agentic frameworks.
  • Architect multi-step reasoning systems.
  • Lead decisions on deterministic workflows vs. autonomous agents.
  • Implement guardrails, safety layers, and traceability mechanisms.
  • Develop evaluation frameworks to measure reasoning quality, hallucination rates, and reliability.
  • Establish CI/CD standards for ML lifecycle management.
  • Ensure compliance with enterprise data governance and responsible AI standards.

Requirements
  • 10 + years of Machine Learning/Software Engineer experience
  • Master's degree or bachelor's degree, computer science degree is highly desirable.
  • Strong software engineering background with experience in building system design, architecting AI feature/products that caters large number of users and deals with large volume of unstructured data
  • Experience with ML deployment to production
U.S. National Base Pay Range: $136,100 - $252,800. Geographic differentials may apply in some locations to better reflect local market rates.This job is eligible for an annual incentive bonus.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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