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Google Cloud Machine Learning Engineer Jobs in Frederick, MD

Machine Learning Tutor

Leesburg, VA ยท 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 ...

Machine Learning Tutor

Rockville, MD ยท 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

See Frederick, MD salary details

$23

$62

$86

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

As of Aug 27, 2026, the average hourly pay for google cloud machine learning engineer in Frederick, MD is $62.53, according to ZipRecruiter salary data. Most workers in this role earn between $53.32 and $71.20 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 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 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 job categories do people searching Google Cloud Machine Learning Engineer jobs in Frederick, MD look for?

The top searched job categories for Google Cloud Machine Learning Engineer jobs in Frederick, MD are:

Infographic showing various Google Cloud Machine Learning Engineer job openings in Frederick, MD as of July 2026, with employment types broken down into 93% Full Time, 3% Part Time, and 4% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $130,053 per year, or $62.5 per hour.

Staff Machine Learning Engineer - Generative AI

Xometry

Gaithersburg, MD โ€ข Hybrid

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 19 days ago


Job description

Xometry is seeking a Staff Machine Learning Engineerย to lead our Generative AI efforts. This is a rare opportunity to shape the future of manufacturing by applying cutting-edge AI research to real-world problems: from multimodal document understanding, to extracting structured data from technical drawings, to building new ways of reasoning across text, images, and 3D data. If you're passionate about building state-of-the-art AI systems and want to see your work have immediate business and customer impact, we'd love to talk.

How You'll Contribute:

  • Lead with vision - Set the technical direction for our Generative AI team, establish best practices, and inspire high-impact innovation
  • Drive strategy - Help shape the AI roadmap, identifying the most valuable opportunities to apply generative AI across Xometry's marketplace
  • Build cutting-edge models - Develop and deploy large language and generative models for multimodal document processing and structured data extraction
  • Innovate across modalities - Explore new ways to combine text, images, and 3D data to unlock smarter, faster solutions
  • Engineer at scale - Create data pipelines and training workflows that can handle massive, complex datasets
  • Deploy in the cloud - Use AWS and other platforms to train, optimize, and deploy models into production at scale
  • Collaborate widely - Work with engineers, product leaders, and business teams to bring AI solutions into real products and customer workflows
  • Mentor and grow - Guide teammates on advanced ML methods, model architecture, and best practices, elevating the entire team
  • Stay ahead - Keep up with the latest generative AI and deep learning research, and bring fresh ideas into production

What You'll Bring to Xometry:

  • Bachelor's degree required; advanced degree (M.S. or PhD) in Computer Science, Machine Learning, AI, or related field is a big plus
  • 5+ years of experience in machine learning or data science, with deep expertise in generative models, LLMs, or computer vision
  • Strong track record working with large-scale language and vision models (Transformers, GPT, VLMs)
  • Hands-on experience with multimodal data (text, images, 3D)
  • Proficiency in Python and key ML libraries (PyTorch, TensorFlow, pandas, NumPy)
  • Solid grounding in probability, statistics, and optimization for generative modeling
  • Experience deploying ML and AI models using cloud microservice architecture (AWS preferred)
  • Strong software engineering skills, including object oriented programming, testing, version control, CI/CD best practices and IaC (terraform preferred)
  • A proven ability to communicate effectively with all levels of the organization, from executives to product managers and various stakeholders
  • Background in manufacturing, supply chain, or related industries is a plus - but curiosity and drive matter more
  • Must be a U.S. Citizen or Green Card holder (ITAR compliance)

The estimated base salary range for new hires into this role is $140,000-$230,000 annually + bonus depending on factors such as job-related skills, relevant experience, and location. ย We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.

#LI-Hybrid


Xometry logo

About Xometry

Sourced by ZipRecruiter

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.

Industry

Software development

Company size

501 - 1,000 Employees

Headquarters location

Gaithersburg, MD, US

Year founded

2013