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Ai Model Trainer Jobs in Indiana (NOW HIRING)

Pwc

AI Engineer

Indianapolis, IN · On-site

$50K - $112K/yr

... the AI models to be useful and scalable. As an Associate, you will focus on learning and ... training and/or progressively responsible work experience in Engineering with AI and Machine ...

Precinmac

AI Engineer

Indianapolis, IN · On-site

Ensure proper data handling, model training infrastructure and deployment. Authorities: Not applicable . Duties: * Influence AI strategy and help drive AI adoption. * Establish secure, scalable, and ...

micro1 AI

AI Training Specialist - Chemistry

Carmel, IN · Remote

$70 - $90/hr

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... training datasets and reasoning capabilities of AI systems. Preferred Qualifications * Advanced ...

micro1 AI

AI Training Specialist - Chemistry

Fishers, IN · Remote

$70 - $90/hr

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... training datasets and reasoning capabilities of AI systems. Preferred Qualifications * Advanced ...

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All JobsAi Model Trainer JobsAi Model Trainer Jobs in Indiana

Ai Model Trainer information

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How much do ai model trainer jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for ai model trainer in Indiana is $24.46, according to ZipRecruiter salary data. Most workers in this role earn between $18.32 and $28.37 per hour, depending on experience, location, and employer.

What does an AI model trainer do?

An AI Model Trainer is responsible for developing, training, and refining artificial intelligence models using large datasets. They preprocess data, select appropriate algorithms, monitor model performance, and tune parameters to improve accuracy and efficiency. Model trainers often collaborate with data scientists, engineers, and domain experts to ensure the AI meets specific requirements and delivers reliable results. Their work is essential for creating applications like image recognition, natural language processing, and predictive analytics.

What are some typical challenges faced by AI model trainers when working with large datasets?

AI Model Trainers frequently encounter challenges such as ensuring data quality, handling imbalanced datasets, and maintaining data privacy. Working with large datasets often requires careful preprocessing and cleaning to avoid biases and inaccuracies in the model. Additionally, trainers must collaborate closely with data engineers, domain experts, and software developers to validate data sources and to fine-tune models for optimal performance. Addressing these challenges is critical for producing reliable, high-performing AI systems.

What are the key skills and qualifications needed to thrive as an AI model trainer, and why are they important?

To thrive as an AI Model Trainer, you need strong expertise in machine learning, data analysis, and a background in computer science or a related field, often supported by an advanced degree. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with data labeling and annotation tools are essential. Attention to detail, critical thinking, and effective communication help in accurately training and refining AI models while collaborating with diverse teams. These skills ensure that AI systems are trained accurately and efficiently, leading to reliable and ethical AI solutions.

What is the difference between Ai Model Trainer vs Data Scientist?

AspectAi Model TrainerData Scientist
Required CredentialsBachelor's in CS, ML, or related; experience with ML frameworksBachelor's or higher in CS, Statistics, or related; advanced analytics skills
Work EnvironmentHands-on model training, data preprocessing, tuningData analysis, modeling, visualization, reporting
Employer & Industry UsageTech companies, AI startups, research labsTech, finance, healthcare, consulting firms
Search & Comparison IntentUnderstanding roles in AI developmentAnalyzing data to inform decisions

While both roles involve working with data and machine learning, an Ai Model Trainer primarily focuses on training and fine-tuning AI models, whereas a Data Scientist emphasizes analyzing data, building models, and deriving insights. The roles often overlap but serve different stages of AI and data projects.

What are popular job titles related to Ai Model Trainer jobs in Indiana?

For Ai Model Trainer jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Ai Model Trainer jobs in Indiana look for?

The top searched job categories for Ai Model Trainer jobs in Indiana are:

What cities in Indiana are hiring for Ai Model Trainer jobs?

Cities in Indiana with the most Ai Model Trainer job openings:

Ai Model Trainer jobs near you
Infographic showing various Ai Model Trainer job openings in Indiana as of August 2026, with employment types broken down into 2% As Needed, 81% Full Time, 14% Part Time, and 3% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution, with an average salary of $50,878 per year, or $24.5 per hour.

AI Training Specialist - Life Sciences

micro1 AI

Fort Wayne, IN • Remote

$90 - $120/hr

Part-time

Posted 18 days ago

Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative 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 complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.

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