AI ML Engineer - Cybersecurity Applications
AI ML Engineer - Cybersecurity Applications
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Job Description
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 worlds most iconic financial institutions where security is vital.
As a Security Engineer III at JPMorganChase within the Cybersecurity and Technology Controls line of business youserve 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 firms 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 ( scanner) to analyzeand correlate incident data toidentify interpret andsummarize the probability andimpact of threats whendetermining specificvulnerabilities
- Leads delivery of continuity-related awareness training educational activities andexercises
- 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.
Employment Type
Full-Time
