Lead Security Engineer - AI ML Data Scientist

JPMorgan Chase - Columbus, OH

Full-time - Senior

Columbus, OH

Credit Intermediation and Related Activities

About the position

Join a team where you can play a crucial role in shaping the future of a world-renowned company and make a direct and meaningful impact in a space designed for top performers. As a Senior Lead Security Engineer at JPMorgan Chase within the Cybersecurity and Technology Controls organization, you are an integral part of an agile team that works to deliver software solutions that satisfy pre-defined functional and user requirements with the added dimension of preventing misuse, circumvention, and malicious behavior. Drive significant business impact through your capabilities and contributions and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of cybersecurity challenges that span multiple technology domains. In this role, you will create bespoke data models and algorithms tailored to address the Cyber Technology Group's requirements and apply them to data sets while developing and employing the company's A/B testing framework to assess model quality. You will apply advanced principles, theories, and concepts in the realm of Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLMs), Deep Learning (DL), Generative AI, Transfer Learning, and Reinforcement Learning algorithms to cyber data sets. Additionally, you will utilize open-source and third-party models while contributing to the development of innovative AI capabilities. You will coordinate with various functional teams to implement models and track results, establish processes and tools for monitoring model performance and data accuracy, and develop custom models when suitable models are unavailable in JPMC's inventory, from suppliers, or in the open-source domain. Extracting and analyzing data from JPMC data sources will be crucial, as you will evaluate the effectiveness and precision of new data sources and data collection techniques. Your responsibilities will also include assessing and choosing suitable LLM tools and models for diverse tasks, including curating custom datasets and fine-tuning LLMs with a focus on parameter-efficient, mixture-of-expert, and instruction methods. You will design and develop advanced LLM prompts, Retrieval-Augmented Generation (RAG) solutions, and intelligent agents for the LLMs, executing experiments to push the capability limits of LLM models and enhance their dependability. Furthermore, you will orchestrate multiple models and develop innovative approaches for sparse-data situations, facilitate security requirements clarification for multiple networks to enable multi-level security, and work with stakeholders and senior business leaders to recommend business modifications during periods of vulnerability. You will triage based on risk assessments of various threats and manage resources to cover the impact of disruptive events while adding to a team culture of diversity, equity, inclusion, and respect.

Responsibilities

• Create bespoke data models and algorithms tailored to address Cyber Technology Group's requirements and apply them to data sets while developing and employing the company's A/B testing framework to assess model quality.
• Apply advanced principles, theories, and concepts in the realm of Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLMs), Deep Learning (DL), Generative AI, Transfer Learning, and Reinforcement Learning algorithms to cyber data sets.
• Utilize open-source and third-party models while contributing to the development of innovative AI capabilities.
• Coordinate with various functional teams to implement models and track results.
• Establish processes and tools for monitoring model performance and data accuracy and develop custom models when suitable models are unavailable in JPMC's inventory, from suppliers, or in the open-source domain.
• Extract and analyze data from JPMC data sources, evaluating the effectiveness and precision of new data sources and data collection techniques.
• Assess and choose suitable LLM tools and models for diverse tasks including curating custom datasets and fine-tuning LLM with a focus on parameter-efficient, mixture-of-expert, and instruction methods.
• Design and develop advanced LLM prompts, Retrieval-Augmented Generation (RAG) solutions, and Intelligent agents for the LLMs and executing experiments to push the capability limits of LLM models and enhance their dependability.
• Orchestrate multiple models and develop innovative approaches for sparse-data situations.
• Facilitate security requirements clarification for multiple networks to enable multi-level security to satisfy organizational needs.
• Work with stakeholders and senior business leaders to recommend business modifications during periods of vulnerability.
• Triage based on risk assessments of various threats and manage resources to cover the impact of disruptive events.
• Add to a team culture of diversity, equity, inclusion, and respect.

Requirements

• Formal training or certification on security engineering concepts and 5+ years of applied experience in security engineering.
• Deep technical expertise in AI, ML, and cybersecurity methodologies.
• Strong problem-solving skills and the ability to work in an agile team environment.
• Experience with data modeling, algorithm development, and A/B testing frameworks.
• Familiarity with open-source and third-party AI models and tools.

Nice-to-haves

• Experience with Generative AI and Reinforcement Learning algorithms.
• Knowledge of cybersecurity frameworks and best practices.
• Familiarity with risk assessment methodologies and security requirements clarification.