AI Trust Innovation Technologist

The AI Trust Innovation Technologist strengthens SGSs Digital Research & Ventures capabilities by actively building testing and analysing AI systems to develop credible independent validation and monitoring services. The role combines deep AI engineering expertise with venture-oriented innovation evaluating emerging technologies and startups while translating hands-on experimentation into scalable Digital Trust validation solutions.

Key responsibilities:

• Analyse emerging AI technologies and real-world AI system architectures (e.g. LLM-based systems ML pipelines multimodal systems) to identify where independent validation testing or monitoring by SGS is technically feasible and valuable.
• Technically assess AI risks including robustness failures bias/fairness issues explainability limits data integrity risks cybersecurity vulnerabilities and misuse scenarios (e.g. deepfakes hallucinations) and translate them into potential validation or monitoring service opportunities.
• Develop prototype and evaluate AI validation approaches (e.g. adversarial testing dataset validation interpretability methods provenance/watermarking) to assess technical feasibility and scalability for Digital Trust services.
• Interpret AI regulations and standards (e.g. EU AI Act ISO/IEC AI standards NIST AI RMF) and translate their technical implications into viable validation monitoring or independent evaluation approaches.
• Engage with universities AI research labs startups and technology leaders to track cutting-edge AI system developments and explore collaboration experimentation and validation opportunities.
• Assess AI startups tools and platforms for technical maturity architectural soundness evaluation robustness and strategic fit with SGSs AI Trust ambitions.
• Provide technical insight and hands-on validation input for AI-related buildbuypartnerinvest evaluations including assessment of model architectures evaluation methodologies and system scalability.
• Contribute expert insight to Digital Trust marketing thought leadership and internal education on AI trust issues.
• Work cross-functionally with business lines M&A R&D innovation teams and IT to technically assess AI systems prototype validation approaches and support early-stage AI trust initiatives.
• Build and experiment with AI systems directly to deeply understand system behaviour validation challenges and potential service design implications.

Qualifications :

Essential Experience:

• Advanced degree (Masters or PhD) in AI Machine Learning Data Science Computer Science or a related field.
• 25 years of hands-on experience building deploying and validating AI/ML systems in production environments startup environments or advanced R&D settings.
• Strong understanding of AI validation and trust challenges (robustness bias explainability AI security misuse) grounded in practical AI system development experience.
• Practical experience applying AI evaluation and validation methods (e.g. interpretability techniques dataset validation adversarial testing red teaming provenance or watermarking mechanisms).
• Experience working in research-driven startup or advanced AI R&D environments with the ability to translate research concepts into working prototypes.
• Ability to translate deep technical understanding of AI system behaviour into scalable independent validation monitoring or assurance service opportunities.

Desirable Skills:

• Ability to technically analyse and diagnose AI system behaviour and identify validation robustness or monitoring gaps.
• Practical experience applying AI validation and evaluation approaches (e.g. interpretability techniques dataset validation adversarial testing red teaming provenance or watermarking mechanisms).
• Understanding of major AI regulations and standards and their technical implications for AI system validation and monitoring approaches.
• Experience assessing AI startups tools or research from a technical architecture evaluation and system maturity perspective.
• Innovative systems-oriented thinker able to translate technical AI validation challenges into scalable Digital Trust service concepts.
• Collaborative hands-on and comfortable working across research engineering business and venture-building environments.
• Strong experimental mindset with the ability to rapidly prototype and test AI validation concepts.
• Familiarity with AI lifecycle management and MLOps concepts (e.g. monitoring drift detection retraining pipelines) is an advantage.

Additional Information :

Why SGS

• Opportunity to work with a global leader in inspection verification testing and certification.
• Collaborative and inclusive work environment.
• Competitive salary and benefits package.
• Opportunities for professional growth and development.

Join Us: At SGS we are dedicated to fostering an open friendly and supportive culture that thrives on teamwork. We value diversity and provide endless opportunities to learn grow your expertise and fulfil your potential.

The minimum gross annual salary for this position is EUR 62790 (based on 14 monthly payments) according to the applicable collective agreement. A higher salary may be possible depending on your qualifications and experience.

Remote Work :

No

Employment Type :

Full-time