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Generative Ai Testing Jobs in Illinois (NOW HIRING)

James Hardie

Senior AI/ML Solutions Engineer

Chicago, IL · On-site

$57 - $73.50/hr

Design and implement solutions leveraging Generative AI (LLMs, text generation, RAG pipelines) and ... Establish and follow best practices for model deployment, versioning, testing, and observability.

James Hardie

Senior AI/ML Solutions Engineer

Chicago, IL · On-site

$57 - $73.50/hr

Design and implement solutions leveraging Generative AI (LLMs, text generation, RAG pipelines) and ... Establish and follow best practices for model deployment, versioning, testing, and observability.

James Hardie

Senior AI/ML Solutions Engineer

Chicago, IL · On-site

$57 - $73.50/hr

Design and implement solutions leveraging Generative AI (LLMs, text generation, RAG pipelines) and ... Establish and follow best practices for model deployment, versioning, testing, and observability.

Kirkland & Ellis LLP.

AI Innovation Advisor

Chicago, IL · On-site

... generative AI capabilities, limitations, and firm governance requirements. • Coordinate tasks, timelines, and stakeholders for AI workflow development initiatives. Workflow Development & Testing ...

The Hartford

Senior AI Machine Learning Engineer

Chicago, IL · On-site

$126K - $166K/yr

Support the initial build-out of generative AI and agentic AI solutions, including prompt ... Strong hands-on expertise in Python, SQL, SDLC practices, Git-based development, automated testing ...

US Bank

Lead AI Engineer - Observability

Chicago, IL · On-site

$105K - $139K/yr

Job Summary The Lead Engineer (Generative AI) is a senior technical role responsible for designing ... Build and manage CI/CD pipelines supporting automated testing, deployment, and release management

New

US Bank

Lead AI Platform Engineer

Chicago, IL · On-site

$105K - $139K/yr

Job Summary The Lead Engineer (Generative AI) is a senior technical role responsible for designing ... Build and manage CI/CD pipelines supporting automated testing, deployment, and release management

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Generative Ai Testing information

What is generative AI testing?

Generative AI Testing refers to the process of evaluating and validating AI systems, particularly those that generate content such as text, images, or code. This type of testing focuses on assessing the accuracy, reliability, fairness, and safety of generative models to ensure they function as intended and avoid producing harmful or biased outputs. Testers use various methods, including automated and manual techniques, to check for issues like hallucinations, inappropriate content, or security vulnerabilities. The goal is to build trust in generative AI systems and ensure they meet quality and ethical standards before deployment.

What are some common challenges faced when testing generative AI models, and how can I prepare to address them in this role?

Testing generative AI models often involves unique challenges such as evaluating the quality and relevance of generated content, detecting bias or inappropriate outputs, and ensuring model consistency across various prompts. You may work closely with data scientists and engineers to create robust evaluation frameworks and develop automated as well as manual testing strategies. Familiarity with prompt engineering, statistical evaluation techniques, and domain-specific knowledge will help you address these challenges effectively. Proactively staying updated on industry best practices and collaborating with cross-functional teams are key to success in this dynamic field.

What are the key skills and qualifications needed to thrive as a generative AI testing specialist, and why are they important?

To thrive as a Generative AI Testing Specialist, you need a robust understanding of machine learning principles, model evaluation techniques, and a background in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and model evaluation frameworks, as well as experience with automated testing platforms, is typically required. Analytical thinking, attention to detail, and strong communication skills help you identify model weaknesses and collaborate effectively with development teams. These skills are crucial to ensure the reliability, safety, and ethical deployment of generative AI solutions.

What is the difference between Generative Ai Testing vs Data Scientist?

AspectGenerative Ai TestingData Scientist
Required CredentialsKnowledge of AI models, testing tools, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentAI development teams, testing labs, tech companiesResearch labs, tech firms, finance, healthcare
Employer & Industry UsageAI product testing, quality assurance in techData analysis, predictive modeling across industries

Generative Ai Testing focuses on evaluating and validating AI-generated content and models, ensuring quality and accuracy. Data Scientists analyze data, build models, and derive insights. While both roles require programming and AI knowledge, Generative Ai Testing emphasizes testing processes, whereas Data Scientists focus on data analysis and model development.

How do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Relevant certifications and hands-on projects can enhance your qualifications for roles in AI testing environments.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development, focusing on evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, often involving tools like Python and TensorFlow. The role offers opportunities in tech companies and research labs, with demand expected to increase as AI applications expand.

What are popular job titles related to Generative Ai Testing jobs in Illinois?

For Generative Ai Testing jobs in Illinois, the most frequently searched job titles are:

What job categories do people searching Generative Ai Testing jobs in Illinois look for?

The top searched job categories for Generative Ai Testing jobs in Illinois are:

What cities in Illinois are hiring for Generative Ai Testing jobs?

Cities in Illinois with the most Generative Ai Testing job openings:

Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Illinois as of August 2026, with employment types broken down into 60% Full Time, 20% Part Time, and 20% Contract. Highlights an 80% In-person, and 20% Remote job distribution.

Senior Data Scientist Machine Learning & AI

Team Velocity Marketing

Virginia, IL • On-site

$160 - $190/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago

Job description

Senior Data Scientist – Machine Learning & AI

Senior Data Scientist – Machine Learning & AI
Remote | Full-Time | $160,000–$190,000

Team Velocity is seeking a Senior Data Scientist to develop and deploy machine learning, predictive analytics, and AI solutions that improve customer engagement, marketing performance, operational efficiency, and business intelligence.

This is a hands‑on role for an experienced data scientist who can take models from data exploration and development through production deployment, monitoring, and optimization. You will partner with Product, Data Engineering, Software Engineering, Analytics, and business leadership to deliver measurable business impact.

This is a full-time remote position. Candidates must reside in the Continental U.S. and be able to support an 8:30 AM–5:30 PM ET business hours. Eastern and Central Time Zones highly preferred.

KEY RESPONSIBILITIES
  • Design, build, evaluate, and deploy production machine learning models.
  • Develop predictive models for churn, propensity, lead scoring, customer lifetime value, recommendations, forecasting, personalization, and marketing attribution.
  • Perform statistical analysis, hypothesis testing, A/B testing, causal inference, and time-series analysis.
  • Build feature engineering, model training, and inference pipelines.
  • Deploy and monitor ML models, including model performance, drift detection, and retraining.
  • Apply Generative AI, LLMs, RAG, and vector databases to business and customer applications.
  • Partner with Product, Engineering, Analytics, and leadership to translate business problems into scalable data science solutions.
  • Mentor junior data scientists and establish best practices for model development, documentation, and code quality.
REQUIREMENTS
  • Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field; Master's or PhD preferred.
  • 5+ years | Python + SQL | production ML | predictive modeling | model deployment | MLOps | cloud | measurable business impact
  • Proven ability to deliver measurable business impact through data science and machine learning.
  • Strong communication, analytical, and business problem-solving skills.
  • Expert Python and SQL skills.
TECHNICAL EXPERIENCE
  • Statistics: Regression, Bayesian methods, hypothesis testing, experimental design, causal inference, time series
  • Data & Cloud: Snowflake, dbt, Spark, Airflow, GCP preferred; AWS or Azure considered
  • AI/LLMs: OpenAI, Gemini, Claude, LangChain, LangGraph, RAG, embeddings, vector databases
  • Experience with data quality and observability tools such as Great Expectations or Monte Carlo is a plus.

*You do not need experience with every technology listed above. Strong production machine learning experience is the priority.

Preferred Experience
  • Large-scale customer or behavioral data
  • Marketing analytics, personalization, or customer intelligence
  • SaaS, automotive, retail, advertising, or marketing technology
  • Real-time inference or streaming data
  • Production Generative AI applications
COMPENSATION & BENEFITS

The expected salary range is $160,000–$190,000 annually, based on experience, skills, and qualifications. Benefits include medical, dental, vision, 401(k) matching, unlimited paid leave, wellness programs, and more.

About Team Velocity

Team Velocity is a full-service marketing and technology company serving automotive manufacturers and dealerships nationwide. Our proprietary Apollo technology platform uses data, predictive analytics, and AI to predict consumer behavior, personalize marketing, and help dealerships increase sales and service revenue.

Join us in applying data science, machine learning, and AI to real-world business problems at scale.

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