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Ai Model Training Jobs in Hawaii (NOW HIRING)

micro1 AI

AI Training Specialist - Physics

Honolulu, HI · On-site +1

$80 - $150/hr

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

Cymertek Corporation

AI/ML Engineer

Honolulu, HI · On-site

$120 - $160/hr

Familiarity with model optimization methods * Proficiency in deploying models at scale ... Paid Training * No long, wordy reviews with tons of paperwork!!! * Referral bonus program with ...

Cymertek

AI/ML Engineer

Honolulu, HI · On-site

Familiarity with model optimization methods * Proficiency in deploying models at scale ... Paid Training * No long, wordy reviews with tons of paperwork!!! * Referral bonus program with ...

First Hawaiian, Inc.

AI Automation Analyst

Honolulu, HI · On-site

$88K - $115K/yr

This position does not develop machine learning models, train AI models, or own enterprise AI ... Training or certification in Microsoft Power Platform, Power Automate, Copilot Studio, process ...

Cisco

Applied AI Scientist

Honolulu, HI

We combine deep AI research expertise with the scale and operational excellence of Splunk and Cisco ... LargeScale Training & Optimization - Experience optimizing model architectures, distributed ...

Ahtna Incorporated

Estimator - AI

Aiea, HI

$86K - $155K/yr

The Estimator develops and maintains cost models, pricing tools, work breakdown structures, budgets ... Compliance with all company policies and procedures, adhering to company standards for training ...

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Ai Model Training information

What is an AI model training?

An AI Model Training job involves preparing, training, and optimizing machine learning models using data. Professionals in this role preprocess datasets, select appropriate algorithms, adjust model parameters, and evaluate performance to improve accuracy. They work with frameworks like TensorFlow or PyTorch and may fine-tune models for specific tasks such as image recognition or natural language processing. This job requires expertise in data science, programming, and statistical analysis to ensure models perform efficiently in real-world applications.

What are the typical work responsibilities of someone in AI model training?

Professionals in AI Model Training are typically responsible for collecting, preparing, and processing large datasets, designing and implementing machine learning models, and evaluating their performance using statistical methods. You may work closely with data engineers, software developers, and product managers to ensure models meet business objectives and integrate smoothly into existing systems. Regular responsibilities also include tuning hyperparameters, troubleshooting model issues, and staying up-to-date with the latest advancements in AI. This role often involves a mix of independent technical work and collaborative problem-solving sessions with the broader team.

What are the key skills and qualifications needed to thrive in the AI model training position, and why are they important?

To excel in AI Model Training, you need a strong background in machine learning, programming (especially Python), data analysis, and a relevant degree such as computer science or engineering. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud computing platforms, and certifications in AI or data science are highly advantageous. Strong problem-solving skills, attention to detail, and the ability to communicate complex ideas effectively make candidates stand out. These competencies are crucial for developing accurate, efficient AI models and collaborating seamlessly within multidisciplinary teams.

Are there any legit AI model training jobs?

Yes, legitimate AI model training jobs are available in the tech industry, often requiring skills in machine learning, programming (such as Python), and data annotation. These roles can be found at technology companies, research institutions, and through reputable job boards, and may involve tasks like data labeling, model tuning, and algorithm development.

Can you get paid to train AI models?

Yes, AI model training is a paid role that involves developing and fine-tuning machine learning algorithms, often requiring skills in programming, data analysis, and familiarity with tools like TensorFlow or PyTorch. Salaries vary based on experience, location, and the complexity of the models being trained.

How do I become an AI model trainer?

To become an AI model trainer, you typically need a strong background in computer science, machine learning, or data science, often with a bachelor's or master's degree. Skills in programming languages like Python, experience with machine learning frameworks such as TensorFlow or PyTorch, and understanding of data preprocessing are essential. Gaining hands-on experience through projects or internships can also improve your prospects in this role.

What are the most commonly searched types of Ai Model Training jobs in Hawaii?

The most popular types of Ai Model Training jobs in Hawaii are:

What are popular job titles related to Ai Model Training jobs in Hawaii?

For Ai Model Training jobs in Hawaii, the most frequently searched job titles are:

What job categories do people searching Ai Model Training jobs in Hawaii look for?

The top searched job categories for Ai Model Training jobs in Hawaii are:

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Cities in Hawaii with the most Ai Model Training job openings:

Ai Model Training jobs near you
Infographic showing various Ai Model Training job openings in Hawaii as of August 2026, with employment types broken down into 67% Part Time, and 33% Contract. Highlights an 67% In-person, and 33% Remote job distribution.

AI Training Specialist - Cheminformatics

micro1 AI

Honolulu, HI • Remote

$80 - $110/hr

Part-time

Posted 20 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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