Principal Machine Learning Engineer (DLP)

About the Role

Key Responsibilities

• Develop AI-driven solutions using state-of-the-art machine learning, natural language processing, and deep learning techniques including large language models to analyze structured and unstructured datasets, classify documents, extract insights, and detect nuanced patterns.
• Enhance AI accuracy and reliability by leveraging advances in deep learning and NLP to build scalable models that optimize precision, minimize false positives and negatives, and improve the overall product experience.
• Lead end-to-end machine learning implementation by architecting and owning scalable, efficient, and maintainable ML pipelines, ensuring seamless integration with production systems.
• Drive ML innovation and best practices by acting as a technical leader, championing experimentation, deployment strategies, and ML best practices across teams.
• Identify high-impact opportunities by discovering novel applications of AI/ML to solve complex data security and privacy challenges, shaping a high-value roadmap.
• Collaborate with cross-functional teams including Product, Engineering, and Business to align ML advancements with strategic goals and drive innovation in Data Security and Data Loss Prevention solutions.

Requirements

• MS or PhD in Computer Science, Mathematics, Statistics, or a related field, or equivalent military experience.
• 5+ years of industry or academic experience in software development, with at least 2 years as a machine learning engineer, data scientist, or LLM specialist.
• Strong programming skills with experience in distributed cloud systems (GCP, AWS, Azure) and containerization technologies like Docker and Kubernetes.
• Proven ability to solve real-world problems using machine learning, deep learning, and generative AI techniques.
• Experience with deep learning frameworks such as PyTorch and TensorFlow, NLP models like transformers, BERT, GPT, and Retrieval-Augmented Generation (RAG).
• Proficiency in ML algorithms including XGBoost, CatBoost, CNNs, LSTMs, and NLP frameworks like spaCy, Gensim, NLTK, and tokenization techniques.
• Strong understanding of ML Ops, model evaluation, fine-tuning, prompt engineering, and deployment best practices.
• Hands-on experience building and optimizing LLM-powered applications, vector search systems, and multimodal AI solutions.
• A 'get stuff done' attitude, thriving in a fast-paced, collaborative environment, and leading cutting-edge AI initiatives.
• Passion for security and AI-driven threat detection; prior experience in NLP, cybersecurity, or data protection products is a plus.

Nice to Have

• Experience with security and threat detection applications.
• Prior experience in NLP, cybersecurity, or data protection products.

Qualifications

• Educational background with MS or PhD in relevant fields or equivalent military experience.
• Minimum of 5 years in software development, with at least 2 years focused on machine learning, data science, or LLMs.

Benefits & Perks

• Compensation between $136,000 and $215,000 per year, depending on qualifications and experience.
• Potential inclusion of restricted stock units and bonuses.
• Flexible wellbeing spending account with over 1,000 eligible items.
• Mental and financial health resources.
• Personalized learning opportunities.