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Freelance Google Machine Learning Engineer Jobs (NOW HIRING)

Booz Allen Hamilton

Machine Learning Engineer

Aurora, CO · On-site

$78 - $176/hr

As a machine learning engineer on our space team, you'll train, test, deploy, and maintain models ... Experience with operationalizing software in the cloud such as AWS, Microsoft Azure, or Google

Flexjet

Machine Learning Engineer

Cleveland, OH · On-site

POSITION SUMMARY Flexjet is seeking a motivated Entry-Level Machine Learning Engineer to join our ... Exposure to cloud platforms (AWS, Azure, or Google Cloud) * Basic understanding of APIs or web ...

Flexjet

Machine Learning Engineer

Cleveland, OH · On-site

POSITION SUMMARY Flexjet is seeking a motivated Entry-Level Machine Learning Engineer to join our ... Exposure to cloud platforms (AWS, Azure, or Google Cloud) * Basic understanding of APIs or web ...

Leash Bio

Machine Learning Engineer

Salt Lake City, UT · On-site

They are seeking a highly skilled Machine Learning Engineer to manage large datasets, optimize ... Google Cloud, with flexibility to other platforms). • Collaborate closely with ML researchers ...

Flexjet

Machine Learning Engineer

Cleveland, OH

POSITION SUMMARY Flexjet is seeking a motivated Entry-Level Machine Learning Engineer to join our ... Exposure to cloud platforms (AWS, Azure, or Google Cloud) * Basic understanding of APIs or web ...

Tapestry

Machine Learning Engineer

Mountain View, CA · On-site

About Tapestry Tapestry is a group within Google working to build the AI-powered electric grid. We ... About the role: We're looking for an early career Machine Learning Engineer to join our team. In ...

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Freelance Google Machine Learning Engineer information

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

As of Aug 26, 2026, the average hourly pay for freelance google machine learning engineer in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What does a freelance Google Machine Learning Engineer do?

A Freelance Google Machine Learning Engineer is a technical specialist who designs, develops, and deploys machine learning models using Google’s tools and platforms, such as TensorFlow and Google Cloud AI services. They work independently or with clients to solve data-driven problems, build predictive models, and automate processes using machine learning techniques. Their responsibilities may include data preprocessing, feature engineering, model training and evaluation, and integrating models into production systems. Freelancers often manage multiple projects and must stay updated on the latest ML advancements and Google technologies.

What are the key skills and qualifications needed to thrive as a freelance Google Machine Learning Engineer?

To thrive as a Freelance Google Machine Learning Engineer, you need a solid background in computer science, statistics, and machine learning, typically supported by a relevant degree and experience with real-world data projects. Familiarity with Google Cloud Platform (GCP), TensorFlow, and certifications like Google Professional Machine Learning Engineer are commonly required. Strong problem-solving abilities, self-motivation, and effective client communication distinguish top freelancers in this field. These skills and qualifications are crucial for delivering robust machine learning solutions tailored to client needs and efficiently navigating remote, project-based work.

What are some common challenges freelance Google Machine Learning Engineers face when working with clients remotely?

Freelance Google Machine Learning Engineers often encounter challenges such as clearly defining project scopes, aligning on deliverables, and managing expectations, especially when working remotely. Communication can be more complex due to time zone differences and varying levels of technical understanding among clients. Staying updated with Google’s latest ML tools and ensuring secure, efficient data sharing are also important. Building strong documentation and regular progress updates can help foster trust and smooth collaboration.

What is the difference between Freelance Google Machine Learning Engineer vs Freelance Data Scientist?

AspectFreelance Google Machine Learning EngineerFreelance Data Scientist
CredentialsKnowledge of Google Cloud ML tools, programming skills in Python, TensorFlowStatistical expertise, programming in Python/R, data analysis skills
Work EnvironmentCloud platforms, AI/ML projects, collaboration with developersData analysis, reporting, model development, client communication
Industry UsageTech companies, AI startups, cloud service providersFinance, healthcare, marketing, research organizations

While both roles involve working with data and models, a Freelance Google Machine Learning Engineer specializes in deploying ML solutions on Google Cloud, focusing on AI/ML engineering tasks. A Freelance Data Scientist primarily analyzes data, builds statistical models, and provides insights. The roles overlap in skills but differ in focus and tools used.

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Freelance Google Machine Learning Engineer jobs near you
Infographic showing various Freelance Google Machine Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.

Machine Learning Engineer

Annapolis Junction, MD • On-site

Cymertek Corporation
IT Services • 11 - 50 employees
Learn more about Cymertek Corporationexternal

Full-time

Re-posted 21 days ago

Job description

Job Summary:
Cymertek Corporation is seeking a talented and innovative Machine Learning Engineer to join their team and help build intelligent systems that drive impactful business solutions. In this role, you will work with cutting-edge technologies to design, develop, and deploy machine learning models that solve complex problems and improve decision-making processes.
Responsibilities:
• Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
• Ability to design, implement, and optimize machine learning models and workflows
• Experience working with large, complex datasets
• Knowledge of data preprocessing and feature engineering
• Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
• Strong problem-solving skills and analytical thinking
Qualifications:
Required:
• Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning)
• Ability to design, implement, and optimize machine learning models and workflows
• Experience working with large, complex datasets
• Knowledge of data preprocessing and feature engineering
• Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure)
• Strong problem-solving skills and analytical thinking
• Proficiency in programming languages (e.g., Python, R, Java)
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
• Expertise in model evaluation techniques and metrics
• Strong knowledge of version control tools (e.g., Git)
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau)
• Understanding of database technologies (e.g., SQL, NoSQL)
• Bachelor's Degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, Statistics, Software Engineering, Electrical Engineering, Robotics, Computational Biology, Physics, etc.
Preferred:
• Experience with natural language processing (NLP)
• Knowledge of deep learning techniques (e.g., CNNs, RNNs)
• Familiarity with deployment tools (e.g., Docker, Kubernetes)
• Experience with data augmentation and synthetic data generation
• Ability to collaborate in cross-functional teams (e.g., engineers, product managers)
• Knowledge of edge computing and model optimization for deployment
Company:
With headquarters in Maryland, Cymertek [/'sī-mer-tek/] Corporation provides superior consulting services for the implementation of high quality information systems. Founded in 2010, the company is headquartered in Laurel, USA, with a team of 11-50 employees. The company is currently Early Stage.

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