Sr Lead Security Engineer - AI ML

As a Senior Lead Security Engineer at JPMorgan Chase within the cyber and tech controls line of business, 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.

We anticipate that the ideal candidate will possess a high level of proficiency in Deep Learning and GenAI model development, training, and tuning in addition to MLOps lifecycle management and be adept at data curation and preparation, as well as utilizing public cloud platforms and optimizing and operationalizing the model effectively.

• 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 AI/ML/DL, GenAI, 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 but not limited to curating custom datasets and fine-tune LLM with a focus on parameter-efficient, mixture-of-expert, and instruction methods designing and developing 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
• Facilitates security requirements clarification for multiple networks to enable multi-level security to satisfy organizational needs
• Works with stakeholders and senior business leaders to recommend business modifications during periods of vulnerability
• Triages based on risk assessments of various threats and managing resources to cover impact of disruptive events
• Adds to team culture of diversity, equity, inclusion, and respect

• Formal training or certification on security engineering concepts and 5+ years applied experience
• Have experience in developing ML pipelines, including data gathering from system records, data preparation (data analysis and preprocessing), model selection, training, testing, validation, and prediction
• Be proficient in using algorithms such as Linear Regression, Logistic Regression, Decision Tree, Random Forest, Bagging and Boosting, K-Nearest Neighbor, Support Vector Machine, Single Layer Perceptron, Multi-Layer Perceptron, Feed Forward, CNN, RNN, LSTM, GRU, BERT, Hugging Face and Spacy Models, Naive Bayes, Markov-Model, Graph Models, and more
• Have experience in backend development, including databases (SQL/No
  
  SQL/Graph), programming languages (Python/Java/Node.js), web frameworks, APIs, and microservices and possess front-end development skills, including HTML, CSS, and JavaScript, and familiarity with frameworks such as React or Angular
• Demonstrate a solid understanding of statistical theory, data mining, or machine learning algorithms. Understand advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and have experience applying them
• Have expertise in Python, SQL, and Spark for developing large-scale applications using extensive datasets and have experience working with and creating data architectures
• Skilled in planning, designing, and implementing enterprise-level security solutions
• Advanced knowledge of software application development and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• Extensive experience with threat modeling, discovery, vulnerability, and penetration testing
• Ability to tackle design and functionality problems independently with little to no oversight
• Practical cloud native experience

• Experience in managing GPU and compute resources in frameworks like PyTorch or Tensor Flow and proficiency in coding with multiple languages, including C, C++, and…