SecurityScorecard - Senior Machine Learning Engineer

• Model Development & Deployment: Design and optimize LLM-based models, algorithms, and agents, then deploy them into production environments with a focus on scalability, reliability, and performance. • LLM & Multi-Agent Systems: Develop and maintain advanced LLM-powered systems and multi-agent architectures to automate and accelerate cybersecurity risk assessment workflows. This includes designing conversational AI agents, orchestrating interactions between multiple agents, and building and integrating scalable RESTful APIs and microservices to expose model capabilities for integration with broader product ecosystems. • Performance Monitoring: Supporting observability and evaluation of LLM-based agents to ensure long-term model accuracy, robustness, and stability. • Data Pipeline Creation: Build and maintain scalable data pipelines to preprocess, clean, and transform raw data for analysis and model training. • Research and Experimentation: Stay updated on the latest agent, LLM, and ML techniques, tools, and frameworks to enhance model accuracy and efficiency. • Collaboration: Work closely with data scientists, ML engineers, software engineers, and product teams to understand requirements and integrate ML solutions into products. • Documentation: Create clear and concise documentation for models, processes, and systems to support team collaboration and knowledge sharing.