AI Consultant - AI Testing & Trustworthy AI

On behalf of our partners we are seeking a dynamic AI Consultant, specializing in AI Testing and Trustworthy AI, to join an innovative and collaborative team.

This role offers a unique opportunity to work at the intersection of client-facing consulting and internal product innovation. You will support code4thought clients in assessing, validating, and improving their AI systems, while also contributing to the development of a cutting-edge platform for AI reliability and trustworthiness.

Ideal candidates will have a minimum of three (3) years of experience in AI, data science, or machine learning, and a strong interest in AI governance, auditing, and compliance.

In this position, you will gain hands-on experience in model validation, bias testing, explainability, and performance evaluation while collaborating with clients across various industries. You will also contribute to enhancing internal methodologies and tools that support AI trustworthiness, reliability, and compliance.

This is a hands-on, impactful role for someone who thrives in fast-paced, cross-functional environments and wants to help define the future of responsible AI.

• Client Engagement: Partner with clients to understand their AI testing and evaluation needs, translating them into actionable solutions
• AI Testing & Validation: Design and implement AI testing approaches as proofs of concept (PoCs) within even short timeframes (2–3 weeks), focusing on performance, bias, explainability, and regulatory compliance
• Communication & Reporting: Communicate findings (technical reports, or presentations) and recommendations to diverse audiences, including technical and non-technical stakeholders
• Product & Service Enhancement: Collaborate with internal Product Team to propose new features for our AI testing platform and refine consulting services based on project learnings

• Operational Excellence in AI standards: Stay updated on emerging AI regulations, industry standards, and best practices, actively contributing to the AI auditing community through knowledge sharing and thought

Experience

• 3+ years of hands-on experience in designing, building, and deploying AI-driven solutions, with a proven history of successful contribution.

• Experience in AI quality assurance, model validation, or software testing frameworks is a plus.
• Familiarity with AI model’s validation, bias detection, explainability, and performance metrics.
• Experience in consulting, client engagements, or cross-functional collaboration is highly desirable.

Technical Skills

• Expertise in Python and widely used machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch, LangChain, DeepEval).

• Familiarity with AI evaluation concepts and hands-on experience using fairness and explainability tools (e.g., IBM AI Fairness 360, SHAP, LIME).
• Solid understanding of the ML/AI lifecycle, with exposure to standardized MLOps and AIOps practices.
• Knowledge of at least one AI domain: Natural Language Processing, Computer Vision, Reinforcement Learning, or Generative AI.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization tools (e.g., Docker, Kubernetes).

Soft Skills

• Analytical Thinking: Ability to apply structured AI testing methodologies to real-world business challenges with a structured approach.
• Communication: Skilled at conveying complex technical insights and presenting complex ideas clearly and persuasively to diverse stakeholders.
• Agility: Adaptability and eagerness to operate in a fast-moving and evolving environment.
• Growth Mindset: Eagerness to learn and expand expertise in AI Auditing, and Risk Management.
• Proactivity & Collaboration: Maintains a self-driven approach, excelling both independently and in cross-functional team environments.

Education

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Software Engineering, Mathematics, Statistics, or closely related fields.
• Degrees in Engineering, Physics, Computational Sciences, or related disciplines combined with practical AI experience will also be considered.
• Supplementary training or certifications in ML development, AI system design, AI ethics, responsible AI, or regulatory compliance are a valuable asset.

Preferred Qualifications

• Practical experience in AI model validation, testing, and debugging across various stages of the model lifecycle.
• Familiarity with data preprocessing, bias mitigation techniques, or explainable AI methods.
• Exposure to MLOps/AIOps practices, model monitoring, or AI governance frameworks for managing production-grade AI systems.
• Awareness of AI regulatory and compliance frameworks, such as the EU AI Act, GDPR, or NYC Local Law 144.
• Proficiency with at least one AI assessment or interpretability tool, such as SHAP, LIME, or IBM AI Fairness 360.
• Experience working in consulting environments or in client-facing roles is advantageous.
• Contributions to AI/ML research publications or open-source projects are highly valued.

• Competitive Remuneration packadge
• Hybrid model but above all the below
• Work on meaningful projects shaping the future of ethical AI
• Collaborate with a diverse and passionate team of AI experts, and researchers
• Take the opportunity to grow your skills in a high-impact, forward-looking space