1

Artificial Intelligence Trainer Jobs (NOW HIRING)

What We Look For In a Artificial Intelligence (AI) Tutor * Advanced Subject Mastery: Deep knowledge ... Skilled at breaking down neural network architectures, training optimization, and model evaluation ...

next page

Showing results 1-20

Artificial Intelligence Trainer information

See salary details

$13

$31

$63

How much do artificial intelligence trainer jobs pay per hour?

As of Jun 30, 2026, the average hourly pay for artificial intelligence trainer in the United States is $31.24, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $35.58 per hour, depending on experience, location, and employer.

How much money do AI trainers make?

AI trainers typically earn between $50,000 and $120,000 annually, depending on experience, location, and the complexity of the projects. Entry-level positions may start lower, while experienced trainers with specialized skills in machine learning and data annotation can earn higher salaries.

How do I become an AI trainer?

To become an AI trainer, you typically need a background in computer science, data science, or related fields, along with strong skills in machine learning, programming (such as Python), and data annotation. Gaining experience with AI tools, understanding data labeling processes, and obtaining certifications in AI or machine learning can enhance your qualifications. Practical experience in training models and working with large datasets is also valuable for this role.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles such as AI executives, senior data scientists, or specialized machine learning engineers with extensive experience and advanced skills. These positions often involve leadership, strategic planning, or cutting-edge research, and may require advanced certifications and a strong portfolio of successful projects.

What is an Artificial Intelligence Trainer job?

An Artificial Intelligence Trainer is responsible for training AI models by curating, labeling, and refining datasets to improve machine learning algorithms. They work closely with data scientists and engineers to fine-tune AI performance, ensuring accuracy and efficiency. This role involves tasks such as annotating data, testing AI outputs, and iterating training processes based on results. AI Trainers are essential in making AI systems more intelligent, reliable, and aligned with real-world applications.

What are the typical daily responsibilities of an Artificial Intelligence Trainer?

Artificial Intelligence Trainers are responsible for preparing and curating high-quality datasets, labeling data, and overseeing the training process for AI models. On a typical day, they may analyze outputs to validate model performance, collaborate with data scientists and engineers to refine model accuracy, and document model iteration processes. Trainers also provide feedback on data quality and help develop guidelines to improve consistency and accuracy across datasets. Regular communication with cross-functional teams is key to ensuring project milestones are met and the AI solutions being developed are both robust and reliable.

Is AI trainer a legitimate job?

An AI trainer is a legitimate role involving training artificial intelligence systems through tasks like data labeling, model evaluation, and providing feedback to improve AI performance. It often requires skills in data management, understanding of machine learning concepts, and familiarity with tools like annotation platforms. This job is commonly found in tech companies, research labs, and AI development environments.

What are the key skills and qualifications needed to thrive in the Artificial Intelligence Trainer position, and why are they important?

To thrive as an Artificial Intelligence Trainer, you need a solid understanding of machine learning concepts, data annotation processes, and experience with relevant programming languages such as Python. Familiarity with AI training tools, annotation platforms, and certifications in data science or machine learning are commonly required. Outstanding attention to detail, strong communication skills, and collaborative teamwork abilities help individuals excel in this position. These skills and qualities ensure that AI models are effectively trained, refined, and deployed to meet organizational and project objectives.

What cities are hiring for Artificial Intelligence Trainer jobs? Cities with the most Artificial Intelligence Trainer job openings:
What are the most commonly searched types of Artificial Intelligence Trainer jobs? The most popular types of Artificial Intelligence Trainer jobs are:
What states have the most Artificial Intelligence Trainer jobs? States with the most job openings for Artificial Intelligence Trainer jobs include:
What job categories do people searching Artificial Intelligence Trainer jobs look for? The top searched job categories for Artificial Intelligence Trainer jobs are:
Infographic showing various Artificial Intelligence Trainer job openings in the United States as of June 2026, with employment types broken down into 90% Full Time, 8% Part Time, and 2% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $64,984 per year, or $31.2 per hour.
Artificial Intelligence Engineer

Artificial Intelligence Engineer

Stefanini Group

Dearborn, MI • Hybrid

Contractor

This job post has expired today. Applications are no longer accepted.


Job description

Stefanini Group is hiring!

Stefanini is looking for an Artificial Intelligence Engineer (Dearborn, MI)

For quick apply, please reach out to Fardeen Ali at 248-582-6473/Fardeen.ali2@stefanini.com

We are seeking an AI Engineer to support AI and ML engineering capability within the TOP platform, including model fine-tuning oversight, agentic orchestration architecture, and LLM evaluation. Oversee vendor fine-tuning of Google Cloud Vertex AI using proprietary diagnostic data, ensuring compliance with IP protection requirements and model weight storage architecture

Responsibilities

  • Design and build Orchestration Layer. The integration framework that connects external AI engine with other internal AI engines and TOP platform services 
  • Evaluate AI engine outputs against defined accuracy, latency, and first-time fix rate metrics; drive iterative improvement through structured feedback loops 
  • Define model evaluation frameworks and acceptance criteria for AI-generated triage recommendations, ensuring clinical accuracy before dealer-facing deployment 
  • Build internal tooling for model monitoring, drift detection, and retraining triggers within GCP environment 
  • Collaborate with data engineering team to define data preparation and feature engineering requirements that support model fine-tuning and inference quality 
  • Partner with the GCP Cloud Engineers to ensure model artifact storage, versioning, and access controls comply with IP and security policies 
  • Contribute to the long-term insourcing roadmap by documenting model architectures, training pipelines, and prompt frameworks in sufficient detail to enable internal replication 
Represent AI and ML engineering in architecture reviews and vendor technical discussions.

Experience Required

  • 5 or more years of professional experience in machine learning engineering, AI systems development, or applied AI research 
  • Hands-on experience fine-tuning LLMs in a cloud environment, with specific preference for Google Cloud Vertex AI or equivalent managed ML platforms 
  • Demonstrated experience building agentic AI systems using frameworks such as LangChain, LangGraph, Google Agent Builder, or equivalent orchestration tooling 
  • Machine Learning – 3–5 years of applied ML experience including feature engineering, model selection, training, validation, and deployment. Candidate should be comfortable working with both structured and unstructured data in the context of real-world engineering or automotive telemetry use cases
  • 3–5 years writing production-quality Python for data engineering, ML pipeline development, or platform tooling. Proficiency with relevant libraries such as Pandas, NumPy, scikit-learn, and TensorFlow is expected, along with familiarity with code quality practices such as testing and version control. 
  • 3–5 years of experience designing or working with AI systems, including the application of large language models, expert systems, or intelligent automation within developer or data workflows. Candidate should understand model lifecycle management, prompt engineering, and responsible AI practices
  • Proficiency in Python and ML development tooling including Hugging Face, PyTorch or TensorFlow, and MLflow or Vertex AI Experiments 
  • Experience designing and evaluating LLM outputs for production systems, including prompt engineering, retrieval-augmented generation (RAG) architectures, and model evaluation metrics Strong understanding of MLOps practices including model versioning, deployment pipelines, monitoring, and retraining workflows on GCP 
  • Experience working in regulated or IP-sensitive environments where model artifact ownership and data governance are active concerns 
  • Google Cloud Platform – 2–5 years of hands-on experience with GCP services relevant to AI/ML and data workloads, including Vertex AI, BigQuery, GCS, Dataflow, or Cloud Composer, with the ability to deploy and manage workloads in a production cloud environment

Experience Preferred

  • Experience in automotive diagnostics, vehicle telematics, or connected vehicle platforms. Familiarity with Diagnostic Trouble Code (DTC) data, Over-the-Air (OTA) update systems, or repair order (RO) data structures · Experience with multi-agent AI systems and tool-use patterns in production · Google Cloud Professional Machine Learning Engineer certification

Education Required

  • Bachelor's Degree

Additional Information:

HYBRID / 4 days per week in the office)

**Listed salary ranges may vary based on experience, qualifications, and local market. Also, some positions may include bonuses or other incentives***

Stefanini takes pride in hiring top talent and developing relationships with our future employees. Our talent acquisition teams will never make an offer of employment without having a phone conversation with you. Those face-to-face conversations will involve a description of the job for which you have applied. We will also speak with you about the process, including interviews and job offers.

About Stefanini Group

The Stefanini Group is a global provider of offshore, onshore and near shore outsourcing, IT digital consulting, systems integration, application, and strategic staffing services to Fortune 1000 enterprises around the world. Our presence is in countries like the Americas, Europe, Africa, and Asia, and more than four hundred clients across a broad spectrum of markets, including financial services, manufacturing, telecommunications, chemical services, technology, public sector, and utilities. Stefanini is a CMM level 5, IT consulting company with a global presence. We are a CMM Level 5 company.

#LI-FA1

#LI-ONSITE

Education:Bachelor (BA, BS...)Employment Type: CONTRACTOR