Responsibilities
- Define and execute full-cycle AI initiatives by collaborating with business units to identify use cases, assess data readiness, and select appropriate methodologies.
- Develop and deploy machine learning and generative AI models that deliver tangible business value.
- Build reliable, scalable, and production-grade systems using software engineering principles and MLOps standards.
- Convert business needs into effective AI workflows and system designs.
- Champion code quality, testing rigor, and deployment practices to ensure long-term maintainability.
- Investigate and apply cutting-edge AI methods to address challenging real-world problems.
- Communicate technical strategies clearly, emphasizing practicality, risks, and expected returns.
- Foster trusted relationships with client teams at all levels, from technical staff to leadership.
- Serve as the primary technical authority within project teams.
- Guide junior data scientists through feedback, coaching, and career development support.
- Disseminate knowledge via training sessions, documentation, and peer collaboration.
- Develop internal tools and accelerators to improve project delivery speed and consistency.
- Stay current with emerging technologies and integrate innovative frameworks into practice.
Work Arrangement
Remote (Worldwide) — Paris, Shanghai
Other
- Hiring decisions are based on merit and individual capabilities, with no discrimination on grounds such as belief, gender, age, disability, ethnicity, sexual orientation, political affiliation, religion, union membership, or minority status.
- Dedicated to advancing ethical and inclusive AI through educational programs and research partnerships.
