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Intern Ai Coding Trainer Jobs in Florida (NOW HIRING)

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Intern Ai Coding Trainer information

How does an Intern AI Coding Trainer typically collaborate with senior engineers and learners during a project?

As an Intern AI Coding Trainer, you will often act as a bridge between senior engineers and learners by assisting with coding workshops, answering technical questions, and helping to create or refine training materials. You'll collaborate with senior engineers to understand project requirements and teaching strategies, while also providing learners with hands-on support and feedback. This role offers a dynamic environment where you can develop both your technical and communication skills, and gain valuable insight into AI project workflows.

What is the difference between Intern Ai Coding Trainer vs Intern Data Science Intern?

AspectIntern Ai Coding TrainerIntern Data Science Intern
Required CredentialsBasic programming knowledge, coursework in AI or codingBasic programming, statistics, or data analysis coursework
Work EnvironmentTech companies, educational platforms, AI startupsData-driven companies, research labs, tech firms
Employer & Industry UsageUsed in AI-focused roles, coding bootcamps, online educationCommon in data analysis, research projects, analytics teams

Intern Ai Coding Trainers typically focus on teaching and guiding students or junior developers in AI coding skills, often within educational or tech environments. Intern Data Science Interns work on data analysis, modeling, and research tasks. While both roles require programming knowledge, the AI Coding Trainer emphasizes teaching and training, whereas the Data Science Intern focuses on data-driven project work.

What is an Intern AI Coding Trainer?

Intern AI Coding Trainers are individuals, typically students or recent graduates, who assist in teaching and developing artificial intelligence (AI) and programming skills, often as part of an internship program. They may help design coding exercises, provide feedback to learners, and support classroom or online instruction. Their role often involves learning on the job while contributing to educational projects and gaining experience in both AI and teaching methodologies.

What are the key skills and qualifications needed to thrive as an Intern AI Coding Trainer?

To thrive as an Intern AI Coding Trainer, you need a solid understanding of programming languages (such as Python), foundational knowledge in machine learning concepts, and preferably progress toward a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, Jupyter Notebooks, and version control systems is typically required. Strong communication, patience, and the ability to explain complex technical concepts simply are crucial soft skills for this role. These skills ensure effective training delivery, foster learner engagement, and contribute to the successful development of AI skills in trainees.

What are the most commonly searched types of Ai Coding Trainer jobs in Florida?

The most popular types of Ai Coding Trainer jobs in Florida are:

What cities in Florida are hiring for Intern Ai Coding Trainer jobs?

Cities in Florida with the most Intern Ai Coding Trainer job openings:

Intern Ai Coding Trainer jobs near you

AI Training Specialist - Cheminformatics

micro1 AI

Saint Petersburg, FL • Remote

$80 - $110/hr

Part-time

Posted 13 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

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