As the Applied AI ML Lead - Vice President within the Securities Services Operations division of J.P. Morgan Corporate Investment Bank, you will be a pivotal figure within our AI team. Your role will involve pushing the boundaries of financial applications, spanning from the generation of business intelligence to the development of predictive models and the automation of decision-making processes. You will engage closely with our Securities Services team, employing AI methodologies to address operationally pertinent queries. This position will necessitate the development, articulation, and advocacy for the deployment of AI solutions, the construction of robust, scalable, and reusable AI functionalities, and the proactive tracking of AI trends and technological advancements. Additionally, you will have the opportunity to offer technical mentorship to team members, disseminate best practices, and remain abreast of the latest developments in machine learning.
Job responsibilities
- Spearhead the execution of AI solutions to address complex issues in Securities Services Operations.
- Construct robust, scalable, and reusable AI functionalities.
- Work in tandem with software engineering teams to create and implement Machine Learning services that can be incorporated into key systems.
- Establish a strong partnership with business domain experts, ensuring clear communication and fostering trust with stakeholders.
- Develop both internal and external evaluation metrics to measure model performance in line with business objectives.
- Continually refine existing machine learning models to enhance quality and efficiency.
- Stay updated with the latest AI trends and technologies, utilizing innovative methods to generate business value.
- Offer technical guidance to team members, disseminate best practices, and remain at the cutting edge of advancements in machine learning.
Required qualifications, capabilities and skills
- PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related highly quantitative field.
- Considerable industry experience in an applied Machine Learning or Data Science role.
- Significant hands-on experience developing and deploying Data Science and ML capabilities in production at scale.
- Deep knowledge of machine learning algorithms applied to solving business problems.
- Proficiency in Python and popular Data Science frameworks (e.g. pytorch, pandas, numpy etc) and MLOps platforms (e.g. Sagemaker)
- Experience in fine-tuning, deploying and utilising LLMs in production
- Experience working in highly collaborative environments with complex technical dependencies.
- Proven ability to work effectively in cross-functional teams, collaborating with product managers, engineers, and business leaders, to align AI strategies with organizational goals.
- Strategic mindset with the ability to translate business challenges into AI-driven solutions.
- Excellent communication skills, with ability to articulate complex technical details to non-technical stakeholders.
- Experience mentoring and developing talent within data science and machine learning teams.
Preferred qualifications, capabilities and skills
- Experience with few-shot and zero-shot learning approaches.
- Experience in building RAG systems using LLMs
- Familiar with Agile ways of working and software development life cycle