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Ai Validation Jobs (NOW HIRING)

Stellantis

AI Validation Engineer

Auburn Hills, MI · On-site

We are seeking a Senior AI Validation Engineer to design and implement testing strategies, frameworks, and automated pipelines that ensure the quality, safety, and reliability of deep learning and ...

Stellantis

AI Validation Engineer

Auburn Hills, MI

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

We are seeking a Senior AI Validation Engineer to design and implement testing strategies, frameworks, and automated pipelines that ensure the quality, safety, and reliability of deep learning and ...

Wayve

Systems Engineer, AI Validation

Sunnyvale, CA · Hybrid

$209K - $266K/yr

As a Systems Engineer, you will own a core part of the behavior validation for the Wayve AI Driver, from strategy to implementation and execution. Your contributions will enable the successful ...

Wayve

Systems Engineer, AI Validation

Sunnyvale, CA · On-site

$209K - $266K/yr

As a Systems Engineer, you will own a core part of the behavior validation for the Wayve AI Driver, from strategy to implementation and execution. Your contributions will enable the successful ...

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How much do ai validation jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for ai validation in the United States is $52.00, according to ZipRecruiter salary data. Most workers in this role earn between $39.42 and $63.22 per hour, depending on experience, location, and employer.

What is an AI validation?

An AI Validation job involves testing and verifying artificial intelligence models to ensure they function correctly, reliably, and ethically. This includes evaluating model accuracy, bias, robustness, and compliance with industry standards. AI validation specialists use various techniques such as data validation, performance testing, and adversarial testing to assess AI systems. Their work helps improve model quality, mitigate risks, and ensure AI applications are safe for real-world deployment.

What does an AI validation do?

An AI Validation professional is responsible for evaluating the performance, reliability, and safety of AI models before deployment. This includes designing and executing test cases, analyzing outputs for bias and errors, and documenting results to inform further model refinement. They often collaborate closely with data scientists, engineers, and QA teams to ensure the AI system meets quality and compliance standards. Day-to-day tasks may involve working with datasets, preparing validation reports, and participating in cross-functional review meetings. This role is critical in ensuring that AI systems function as intended in real-world applications.

What are the key skills and qualifications needed to thrive in the AI validation position?

To thrive in AI Validation, you need strong analytical skills, familiarity with machine learning concepts, and typically a degree in computer science, data science, or a related field. Experience with tools such as Python, TensorFlow, PyTorch, and version control systems, as well as knowledge of data annotation and model evaluation frameworks, is highly valuable. Excellent attention to detail, problem-solving skills, and effective communication are important soft skills for success in this role. These competencies are essential to ensure that AI models are robust, accurate, and meet project requirements for deployment.

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Ai Validation jobs near you
Infographic showing various Ai Validation job openings in the United States as of August 2026, with employment types broken down into 63% Full Time, 26% Part Time, and 11% Contract. Highlights an 77% In-person, 3% Hybrid, and 20% Remote job distribution, with an average salary of $108,152 per year, or $52 per hour.

AI Validation Engineer

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 9 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

14th of 44 rated automakers

Job description

As AI-powered features become central to automotive vehicles - from ADAS perception and voice assistants to predictive diagnostics and intelligent infotainment - rigorous validation of these systems is critical for successful deployment. We are seeking a Senior AI Validation Engineer to design and implement testing strategies, frameworks, and automated pipelines that ensure the quality, safety, and reliability of deep learning and LLM-based features across vehicle platforms.
This role sits at the intersection of AI/ML engineering and automotive system validation. You will build the tools, datasets, and evaluation methodologies that enable confident delivery of AI-driven automotive solutions.
Key Responsibilities:
  • Design and implement validation frameworks for deep learning models (perception, NLP, generative AI) deployed in automotive systems, covering accuracy, robustness, latency, and safety metrics.
  • Develop automated test pipelines for LLM-based features, including hallucination detection, response quality evaluation, prompt regression testing, and adversarial input testing.
  • Build and curate evaluation datasets and benchmarks tailored to automotive AI use cases (e.g., voice commands, diagnostic Q&A, sensor fusion outputs).
  • Create AI-assisted test generation tools that leverage LLMs to automatically produce test cases, test data, and expected-result specifications from system requirements.
  • Develop model monitoring and drift detection systems for AI features running in production and test environments.
  • Collaborate with system architects to integrate AI model validation into existing test bench infrastructure and CI/CD pipelines.
  • Implement automated regression testing for ML model updates, ensuring backward compatibility and performance parity across software releases.
  • Analyze test results using statistical methods and ML techniques to identify root causes, failure patterns, and quality trends.
  • Work in cross-functional Agile teams spanning AI/ML, embedded software, and system integration disciplines.

Basic Qualifications:
  • Bachelor's degree in computer science, Machine Learning, Data Science, Electrical Engineering, or a related field.
  • Minimum of 5 years of experience in ML/AI development, with a minimum of 2 years focused on model evaluation, testing, or validation.
  • Strong proficiency in Python and testing/automation frameworks (pytest, Robot Framework, or equivalent).
  • Hands-on experience evaluating deep learning models - including metrics design, dataset curation, bias/fairness analysis, and regression testing.
  • Experience with LLM evaluation techniques (BLEU, ROUGE, human-in-the-loop evaluation, LLM-as-judge approaches).
  • Familiarity with ML experiment tracking and pipeline orchestration tools (MLflow, Weights & Biases, Kubeflow, or equivalent).
  • Experience with CI/CD systems (Jenkins, GitLab CI, GitHub Actions) for automated test execution.
  • Strong analytical and communication skills with the ability to translate AI validation results into actionable insights for engineering teams.

Preferred Qualifications:
  • Master's in Computer Science, Machine Learning, or a related field.
  • Experience with simulation-based testing or digital twin environments.
  • Familiarity with automotive test toolchains (dSpace, Vector CANoe, NI VeriStand) is a plus but not required.
  • Ability to collaborate effectively across time zones with global engineering teams.
  • Knowledge of automotive safety standards (ISO 26262, SOTIF/ISO 21448) as applied to AI systems.
  • Experience with adversarial robustness testing, out-of-distribution detection, or uncertainty quantification for neural networks.

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