Key Responsibilities:
- Hands-On Leadership: Lead by example and actively contribute to the development and delivery of generative AI solutions, driving innovation and excellence within the team.
- Monitoring Ongoing Research: Stay actively engaged in monitoring ongoing research efforts, keeping abreast of emerging trends, and ensuring that the Generative AI team remains at the forefront of the field.
- Model Delivery to Production: Take a hands-on approach to ensure AI models are successfully deployed into production environments, meeting high-quality standards and performance benchmarks.
- Strategy Implementation: Execute the strategy for generative AI research and development, aligning it with the bank's overarching goals and objectives.
- Research and Development: Lead and participate in research activities to explore and advance state-of-the-art generative AI techniques, including GANs, VAEs, and other relevant technologies.
- Cross-Functional Collaboration: Ability to collaborate effectively with various teams, including product managers, engineers, and data scientists, to integrate AI technologies into products and services.
- Quality Control: Ensure the quality and performance of generative AI models, conducting rigorous testing and evaluation.
- Stakeholder Engagement: Work closely with business stakeholders across the bank to drive the adoption of generative AI and Large Language Models, identifying opportunities for innovation and value creation.
- Regulatory Compliance: Ensure that AI initiatives meet regulatory requirements while pushing the boundaries of technology innovation.
Skills & Qualifications:
- Expertise with LLMs: Hands-on experience with Large Language Models and a strong interest in AI.
- Ph.D., master’s or equivalent experience in a relevant field (Computer Science, Machine Learning, etc.).
- Strong experience in Machine Learning, delivering complex solutions to production.
- Proven hands-on experience in data science and Natural Language Processing (NLP), Natural Language Understanding (NLU) and Natural Language Generation (NLG).
- Strong proven delivery track record.
- In-depth knowledge of deep learning frameworks such as TensorFlow, PyTorch, and other open sources libraries / APIs or similar.
- Proficiency in programming languages such as Python.
- Excellent problem-solving skills and the ability to think creatively.
- Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.
- Publications and contributions to the AI research community are a plus.
- Experience in high tech or financial industry is beneficial but not mandatory.
What we’ll provide you
By joining Citi, you will not only be part of a business casual workplace with a hybrid working model (up to 2 days working at home per week), but also receive a competitive base salary (which is annually reviewed), and enjoy a whole host of additional benefits such as:
- 27 days annual leave (plus bank holidays)
- A discretional annual performance related bonus
- Private Medical Care & Life Insurance
- Employee Assistance Program
- Pension Plan
- Paid Parental Leave
- Special discounts for employees, family, and friends
Data Science
Time Type:
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