Principal Machine Learning Engineer

10+ years of experience as a Machine Learning Engineer, with a proven track record of delivering successful projects, along with a solid understanding of machine learning concepts and their applications in cybersecurity
Excellent communication skills with ability to translate complex technical concepts to stakeholders
Strong proficiency in Python, SQL, ML libraries and frameworks
Extensive experience in data modeling, feature engineering, model development, and error analysis
Bachelor’s degree in Computer Science, Engineering, or a related technical field (Master’s Degree or PhD preferred)

Leading the design and development of cutting edge, production ready ML systems and pipelines, cybersecurity applications and providing technical guidance to junior and mid-level engineers
Optimizing existing machine learning pipelines for improved efficiency and scalability
Exploring and experimenting with advanced AI techniques and architectures to solve complex cybersecurity problems as well as staying updated on the latest advancements in AI and applying them to our cybersecurity solutions
Collaborating with cross-functional teams to define project requirements and ensure alignment with business objectives
Ensuring systems and applications meet reliability, scalability and performance requirements

Proven track record of designing, building and shipping end-end applications at scale, with familiarity with multi-agent systems and orchestration frameworks
Strong experience with LLM’s, agent architectures, prompt engineering and SOTA AI frameworks, along with contributions to open-source ML projects, top-tier research publications
Deep expertise with cloud infrastructure (e.g. AWS, GCP) for AI workloads