We are partnering with a leading investment management firm to hire an AI Product Manager to drive the development and adoption of AI-native products in the organisation.
This is a unique opportunity to sit at the intersection of business, technology, and artificial intelligence, partnering with stakeholders that could include investment teams, finance, human resources, risk to identify, prioritize, and deliver high-impact AI solutions that enhance productivity, decision-making, and business outcomes.
...
Functional tests only verify expected behavior, whereas attackers target abnormal, adversarial, and unexpected conditions that lie outside normal workflows.
Many security vulnerabilities emerge in edge cases, error handling paths, and unintended feature interactions, requiring threat-based and robustness testing.
Modern automotive security standards (ISO 21434, CRA, RED-DA) mandate resilience and adversarial validation, making non-functional security testing critical for compliance.
...
Currently pursuing PhD in Computer Science, AI, Mathematics, or a related technical discipline, with a strong foundation in data structures, algorithms, and mathematical modeling.
AI/ML Expertise: Solid understanding and research experience in Deep Learning, NLP, CV, Reinforcement Learning, Generative Models, or Multimodal Learning.
Priority will be given to candidates with publications in international AI/CS conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, KDD, SIGIR, WWW) or top rankings in recognized algorithmic competitions.
...
Participating in all phases of the Talent Acquisition process: gather position requirements from hiring managers and TA Partners, promote open positions via job portals, conduct screening, recruitment, assessment, candidate relationship management, and onboarding process.
Sourcing, targeting, and building pipelines of candidates' databases.
Professional partnering with the TA Partners, hiring managers, and team leaders on hiring needs.
...
Collaborate with cross-functional teams to design, develop, and implement AI features, focusing on areas like natural language processing, data analysis, and predictive modeling.
Conduct research and rapid prototyping of the most suitable AI algorithms and techniques based on best practices, particularly those involving LLMs to address technical and business requirements.
Write clean, well-tested, and well-documented code, contributing to efficient and maintainable system components.
...