AI ML Engineer - Cybersecurity Applications

Your seniority as a security engineer puts you in the ranks of the top talent in your field. Play a critical role at one of the world's most iconic financial institutions where security is vital.

As a Security Engineer III at JPMorganChase within the Cybersecurity and Technology Controls line of business, you serve as a seasoned member of a 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. Carry out critical technology solutions with tamper-proof, audit defensible methods across multiple technical areas within various business functions in support of the firm’s business objectives

Job responsibilities

• Executes security solutions design, development, and technical troubleshooting with the ability to apply knowledge of existing security solutions to satisfy security requirements for internal clients (e.g., product, platform, application owners)
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Applies specialized tools (e.g., vulnerability scanner) to analyze and correlate incident data to identify, interpret, and summarize the probability and impact of threats when determining specific vulnerabilities
• Leads delivery of continuity-related awareness, training, educational activities, and exercises
• Adds to team culture of diversity, opportunity, inclusion, and respect
• Model Development: Design and implement custom data models and algorithms for cybersecurity, using A/B testing to evaluate model quality.
• Advanced AI Techniques: Apply cutting-edge AI/ML/DL methods, including Generative AI, Transfer Learning, and Reinforcement Learning, to enhance cyber data analysis.
• LLM Tools and Development: Lead the selection, fine-tuning, and application development of large language models (LLMs), focusing on innovative LLM-backed applications and advanced methods like Retrieval-Augmented Generation (RAG).
• Collaboration and Implementation: Work with various teams to implement models, monitor outcomes, and ensure data accuracy.
• Innovation and Custom Solutions: Design experiments to push LLM capabilities and develop solutions for sparse-data situations. Create custom models when existing ones are insufficient.
• Security and Risk Management: Facilitate security requirements, recommend business modifications during vulnerabilities, and manage resources based on risk assessments

Required qualifications, capabilities, and skills

• Formal training or certification on Software Engineering concepts and 3+ years applied experience
• Experience developing security engineering solutions
• Proficient in coding in one of more languages
• Overall knowledge of the Software Development Life Cycle
• Solid understanding of agile methodologies such as CI/CD, application resiliency, and security
• Proficiency in developing ML pipelines and using a wide range of algorithms, including deep learning models like CNN, RNN, LSTM, GRU, BERT, and more.
• Strong backend and frontend development skills, with experience in cloud environments (AWS, Google Cloud, Azure).
• Expertise in Python, SQL, and Spark for large-scale applications.
• Advanced knowledge of statistical techniques and machine learning algorithms.
• Experience in enterprise-level security solutions

• Proficiency in managing GPU resources in frameworks like PyTorch or TensorFlow.
• Experience with cloud-native development, CI/CD pipelines, and Agile methodology.
• Familiarity with distributed computing tools like Map/Reduce, Hadoop, and Spark.
• Experience with LLM development and wrapper languages, such as OpenAI and LangChain.
• Proven ability to apply AI to comprehensive and practical technology solutions.