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Title
Text copied to clipboard!Explainable Artificial Intelligence Engineer
Description
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We are looking for a passionate and skilled Explainable Artificial Intelligence Engineer to join our dynamic team. The ideal candidate will be responsible for developing, implementing, and optimizing methods that enhance the transparency, understanding, and trust of users in AI systems. This role is crucial to ensure that AI models are not only performant but also interpretable, ethical, and compliant with current regulations. You will work closely with data scientists, machine learning engineers, ethics experts, and product teams to design explainable solutions tailored to the needs of end-users and stakeholders. Your responsibilities will include analyzing complex models, creating explainability tools, writing clear and educational reports, and training internal teams on best practices in explainable AI. You will also need to stay updated on technological and regulatory advancements in this rapidly evolving field to ensure compliance and continuous innovation. This position requires strong technical expertise, the ability to simplify complex concepts, and a strong commitment to ethics and transparency in artificial intelligence.
Responsibilities
Text copied to clipboard!- Develop and implement explainability methods for AI models.
- Analyze and interpret results of complex models.
- Collaborate with development teams to integrate explainable solutions.
- Write technical and educational reports on AI models.
- Train internal teams on explainability concepts and tools.
- Ensure ethical and regulatory compliance of AI systems.
- Stay updated on technological and scientific advances in explainability.
- Participate in designing user-centered products with transparent AI.
- Test and validate explainability tools.
- Communicate with stakeholders to gather explainability requirements.
Requirements
Text copied to clipboard!- Degree in Computer Science, Artificial Intelligence, Mathematics, or related field.
- Hands-on experience with explainability techniques (LIME, SHAP, etc.).
- Proficiency in programming languages like Python and ML libraries.
- Good understanding of machine learning and deep learning algorithms.
- Ability to simplify complex technical concepts.
- Knowledge of ethical issues related to AI.
- Experience in technical writing and communication.
- Team spirit and good interpersonal skills.
- Ability to work in an agile and multidisciplinary environment.
- Professional English proficiency.
Potential interview questions
Text copied to clipboard!- Which explainability tools have you used before?
- How would you ensure transparency of a complex model?
- Can you explain an explainability method to a non-technical audience?
- How do you integrate ethical considerations into your work?
- Describe a situation where you improved understanding of an AI model.
- How do you stay informed about developments in explainable AI?
- What challenges have you faced in explainability and how did you overcome them?
- How do you prioritize user needs in your solutions?
