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Title

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Artificial Intelligence Explainability Engineer

Description

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We are looking for an Artificial Intelligence Explainability Engineer to join our team and help develop transparent, trustworthy, and ethical AI solutions. In this role, you will work closely with machine learning teams, software developers, and ethics specialists to ensure that our AI models are understandable and explainable to end users, regulators, and stakeholders. Your main responsibility will be to develop and implement model explainability techniques such as LIME, SHAP, counterfactual explanations, and others that enable understanding of AI-driven decisions. You will analyze complex models, create visualizations, and communicate results in a clear and accessible manner. Additionally, you will contribute to the development of internal policies and standards for ethical AI use. The ideal candidate has a strong background in machine learning, statistics, and programming, along with a passion for ethics and the social impact of technology. We expect you to have analytical thinking, excellent communication skills, and a desire to work in a multidisciplinary environment. This position offers the opportunity to be at the forefront of AI innovation and contribute to building more transparent and responsible technologies that serve society.

Responsibilities

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  • Develop and implement AI model explainability techniques
  • Analyze complex models and extract interpretable features
  • Create visualizations and reports to explain models
  • Collaborate with machine learning and ethics teams
  • Develop internal standards for AI transparency
  • Assess the impact of AI decisions on end users
  • Train colleagues on AI explainability concepts
  • Support regulatory compliance efforts
  • Research new interpretability methods
  • Participate in ethical reviews of AI projects

Requirements

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  • Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field
  • Experience with Python and libraries such as scikit-learn, TensorFlow, PyTorch
  • Strong knowledge of statistics and machine learning models
  • Experience with explainability tools such as LIME, SHAP, etc.
  • Understanding of ethical aspects of AI
  • Data visualization skills (e.g., matplotlib, seaborn)
  • Excellent communication and presentation skills
  • Analytical thinking and attention to detail
  • Ability to work in a multidisciplinary team
  • Willingness to learn and apply new technologies

Potential interview questions

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  • What is your experience with AI explainability techniques?
  • Can you describe a project where you used SHAP or LIME?
  • How do you explain a complex model to a non-technical audience?
  • What ethical considerations do you take into account when working with AI?
  • What tools do you use to visualize model results?
  • How do you handle situations where a model is difficult to explain?
  • What is your opinion on AI transparency regulations?
  • What are the challenges in explaining deep neural networks?
  • What motivates you to work in the field of explainable AI?
  • How do you stay informed about new methods and research in this area?