Principal Machine Learning Engineer (DLP)

About the Role

Key Responsibilities

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

Requirements

• MS / 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 (PyTorch, TensorFlow), NLP models (transformers, BERT, GPT), Retrieval-Augmented Generation (RAG), and Large Language Models (LLMs).
• Proficiency in ML algorithms such as 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 proactive, 'get stuff done' attitude, thriving in a fast-paced, collaborative environment while leading AI initiatives.
• Passion for security and AI-driven threat detection, with prior experience in NLP, cybersecurity, or data protection products a plus.

Nice to Have

• Experience with generative AI techniques and large language models (LLMs).
• Experience with vector search systems and multimodal AI solutions.
• Prior experience in cybersecurity, NLP, or data protection products.

Qualifications

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

Benefits & Perks

• Compensation between $151,000 and $246,500 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.