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Freelance Artificial Intelligence Machine Learning Jobs

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Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... Artificial Intelligence (AI)/Machine Learning (ML) models Essential Duties & Responsibilities Research, analyze, support, and implement machine learning solutions on the Snowflake Cloud data ...

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Freelance Artificial Intelligence Machine Learning information

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How much do freelance artificial intelligence machine learning jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for freelance artificial intelligence machine learning 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.

How do freelance AI/ML professionals typically manage client expectations and project scope?

Freelance AI/ML professionals often work with clients who may not fully understand the technical possibilities or limitations of machine learning solutions. A key challenge is clearly communicating what can be achieved within a given timeframe and budget, and then setting realistic milestones. This often involves regular check-ins, well-documented progress updates, and educating clients about the iterative nature of AI/ML development. Building trust and transparency is essential, as is being flexible to adapt project goals based on data availability or evolving client needs.

What are the key skills and qualifications needed to thrive as a Freelance Artificial Intelligence/Machine Learning Specialist, and why are they important?

To thrive as a Freelance Artificial Intelligence/Machine Learning Specialist, you need a strong background in mathematics, statistics, programming (Python or R), and a solid understanding of machine learning algorithms, usually backed by a relevant degree or certifications. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and cloud platforms such as AWS or Google Cloud is typically required. Strong problem-solving abilities, self-motivation, and effective client communication are crucial soft skills for success in freelance work. These skills ensure you can deliver high-quality, innovative solutions independently and maintain strong client relationships in a rapidly evolving field.

What is the difference between Freelance Artificial Intelligence Machine Learning vs Data Scientist?

AspectFreelance Artificial Intelligence Machine LearningData Scientist
CredentialsTypically requires knowledge of AI/ML, programming, and relevant certificationsRequires degrees in data science, statistics, or related fields, often with certifications
Work EnvironmentIndependent, project-based, remote or on-siteUsually employed full-time in organizations, but also freelance options exist
Industry UsageUsed across tech, finance, healthcare, and startups for AI/ML projectsCommon in tech, finance, healthcare, and research sectors for data analysis

Freelance Artificial Intelligence Machine Learning professionals focus on developing AI/ML models independently, often on specific projects, while Data Scientists analyze data to extract insights, typically within organizations. Both roles require strong technical skills, but their work environments and project scopes differ.

What are Freelance Artificial Intelligence Machine Learning professionals?

Freelance Artificial Intelligence (AI) Machine Learning (ML) professionals are independent experts who develop, implement, and optimize AI and ML models for various clients and projects. They often work remotely or on a contract basis, assisting organizations with tasks such as data analysis, algorithm development, model training, and deployment. Freelance AI/ML specialists typically possess skills in programming languages like Python or R, and are familiar with frameworks such as TensorFlow or PyTorch. Their work ranges from building predictive models and automating processes to consulting on AI strategy and integrating machine learning into business solutions.
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Freelance Artificial Intelligence Machine Learning jobs near you
Artificial Intelligence/Machine Learning Oversight Specialist

Artificial Intelligence/Machine Learning Oversight Specialist

Connect Tech+Talent

Austin, TX • Remote

$17.75 - $23/hr

Other

Posted 19 days ago

Job description

Job Description Artificial Intelligence/Machine Learning Oversight Specialist Austin, Texas (Hybrid or Fully remote) Contract (Part Time - 20 hours per week - 500 hours) Minimum: 2+ Years - Production software engineering including: Python backend services async pipeline architecture gRPC/REST API development 2+ Years - Demonstrated ability to build, ship, and maintain systems at scale with measurable performance outcomes 2+ Years - Regression testing framework design and execution 2+ Years - Experience building automated test infrastructure that provides coverage across complex multi-system workflows, including systems not accessible via standard DOM or API selectors 2+ Years - High-volume data pipeline validation including batched ingestion, bulk-load integrity verification, record count reconciliation, and exception identification across large structured datasets 1+ Years - Clear technical communication of system behavior, and quality findings to cross-functional teams including engineers, product managers, and non-technical stakeholders in a structured delivery environment Preferred: 2+ Years - PostgreSQL query optimization, bulk-load performance tuning, and data integrity validation at scale; experience identifying and resolving data quality issues across high-volume ingestion and transformation pipelines 1+ Year - Cross-team code review discipline with demonstrated ability to catch API contract issues, performance regressions, and data integrity risks before production; experience reviewing both backend and frontend pull requests across multi-engineer teams 1+ Year - Experience in a production engineering environment requiring end-to-end ownership of quality outcomes across multiple product teams or customer-facing services; comfort operating across ambiguous, fast-moving technical environments with high accountability

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