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Freelance Artificial Intelligence Machine Learning information

What is a freelance artificial intelligence machine learning professional?

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.

What are the key skills and qualifications needed to thrive as a freelance artificial intelligence machine learning specialist?

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.

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 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 the most commonly searched types of Artificial Intelligence Machine Learning jobs in Tennessee?

The most popular types of Artificial Intelligence Machine Learning jobs in Tennessee are:

What are popular job titles related to Freelance Artificial Intelligence Machine Learning jobs in Tennessee?

For Freelance Artificial Intelligence Machine Learning jobs in Tennessee, the most frequently searched job titles are:

What job categories do people searching Freelance Artificial Intelligence Machine Learning jobs in Tennessee look for?

The top searched job categories for Freelance Artificial Intelligence Machine Learning jobs in Tennessee are:

Freelance Artificial Intelligence Machine Learning jobs near you

Postdoctoral Scholar in Health AI-Pediatrics CBMI

The University of Tennessee

Memphis, TN • On-site

Full-time

Re-posted 10 days ago

Job description

THIS IS A GRANT-FUNDED POSITION FUNDED UNTIL OCTOBER 1, 2027.

The Postdoctoral Scholar designs, develops, evaluates, and optimizes advanced artificial intelligence (AI) methods that support intelligent cancer patient navigation and clinical decision support. Under the direction of the Principal Investigator, this position leads research and development on multimodal machine learning, agentic AI, explainable AI, causal inference, predictive analytics, and continuous learning to develop trustworthy AI solutions that improve cancer care delivery.

Ph.D. in a relevant discipline (e.g. Medical Informatics, Computer Science, Software Engineering, Mathematics, etc.) 

Track record of publications in top journals and conferences in the field. Strong track record of quantitative and analytics mastery, and expertise in Artificial Intelligence, Machine Learning, Causal Modeling, and Knowledge Graphs. Strong coding and implementation skills. Outstanding interpersonal skills and written and verbal communication capabilities.

WORK SCHEDULE: This position may occasionally be required to work weekends and evenings. May require occasional overnight travel. 

  1. Designs, develops, implements, and optimizes advanced artificial intelligence, machine learning, and multimodal AI models for intelligent cancer patient navigation and clinical decision support.

  2. Conducts research in explainable AI, agentic AI, causal inference, predictive analytics, knowledge representation, and continuous learning.

  3. Designs and evaluates AI algorithms using electronic health records, patient-reported outcomes, social determinants of health, medical imaging, and other healthcare data sources.

  4. Conducts benchmarking, validation, performance evaluation, and fairness, robustness, and explainability assessments of AI model.

  5. Collaborates with software engineers, clinicians, and interdisciplinary investigators to translate AI research into interoperable clinical applications and decision support tools.

  6. Develops and maintains reproducible analytical workflows and research software to support AI model development and evaluation

  7. Mentors graduate students and junior researchers throughout the project lifecycle.

  8. Prepares manuscripts, technical reports, conference presentations, and publications in leading journals and scientific meetings.

  9. Participates in proposal preparation and collaborative research activities supporting federally and state-funded research programs.

  10. Performs other duties as assigned.

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