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Freelance Mechanical Engineering Machine Learning Jobs

Vangard, Inc.

Senior Machine Learning Engineer

Malvern, PA · On-site

$102K - $140K/yr

Develop and maintain feature engineering, feature storage, and data preparation pipelines ... Experience in software engineering, machine learning engineering, data engineering, or a related ...

Ksb

Machine Learning Engineer

Grovetown, GA · On-site

Engineering, Research & Development Reports to: Metallurgical and Materials R&D Lab Manager ... Background in CFD, simulation, computational mechanics, or applied physics * Familiarity with ...

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Freelance Mechanical Engineering Machine Learning information

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How much do freelance mechanical engineering machine learning jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for freelance mechanical engineering machine learning in the United States is $33.20, according to ZipRecruiter salary data. Most workers in this role earn between $26.92 and $37.50 per hour, depending on experience, location, and employer.

What is the difference between Freelance Mechanical Engineering Machine Learning vs Freelance Data Scientist?

AspectFreelance Mechanical Engineering Machine LearningFreelance Data Scientist
CredentialsEngineering degrees, certifications in machine learningStatistics, data analysis, programming certifications
Work EnvironmentEngineering firms, manufacturing, product designTech companies, consulting, research labs
Industry UsageProduct development, automation, roboticsData analysis, predictive modeling, business insights

Freelance Mechanical Engineering Machine Learning professionals focus on applying machine learning techniques to mechanical engineering problems, often within manufacturing or product design. In contrast, Freelance Data Scientists analyze data across various industries to generate insights and predictive models. While both roles require machine learning skills, their industry applications and work environments differ significantly.

Can I do freelancing with machine learning?

Freelance mechanical engineering professionals can incorporate machine learning skills to offer specialized services such as predictive modeling, data analysis, and automation solutions. Success in freelancing with machine learning depends on technical expertise, familiarity with tools like Python or TensorFlow, and a strong portfolio to attract clients. Continuous learning and certification can enhance credibility in this competitive field.

Can mechanical engineers work in machine learning?

Mechanical engineers can work in machine learning by applying their knowledge of systems, modeling, and data analysis to develop algorithms for automation, robotics, and predictive maintenance. Gaining skills in programming languages like Python, and understanding machine learning frameworks, can facilitate their transition into this field.
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What are the most commonly searched types of Mechanical Engineering Machine Learning jobs?

The most popular types of Mechanical Engineering Machine Learning jobs are:

What states have the most Freelance Mechanical Engineering Machine Learning jobs?

States with the most job openings for Freelance Mechanical Engineering Machine Learning jobs include:

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Freelance Mechanical Engineering Machine Learning jobs near you
Infographic showing various Freelance Mechanical Engineering Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $69,055 per year, or $33.2 per hour.

Machine Learning Data Scientist - Research Translation & Prototyping

1 point system

New York, NY • On-site

Contractor

Re-posted 8 days ago

Job description

Qualifications:

• Bachelor's degree in a technical field such as computer science, computer engineering or related field required

• 5-7 years’ experience required

• Strong technical foundations in software engineering, machine learning, statistics, and experimental design.

• Experience building data-intensive applications, machine learning systems, experimentation platforms, or AI-powered products.

• Experience evaluating, debugging, and improving machine learning models, data pipelines, and AI-powered applications.

• Experience in programming and experience with problem diagnosis and resolution

• Ability to thrive in ambiguous, rapidly changing environments where requirements evolve through experimentation and discovery.

• Experience with foundation models, generative AI systems, multimodal models, agentic workflows, retrieval-augmented generation (RAG), or related AI technologies.