Senior Machine Learning Engineer, AuditBoard

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field
• 4 plus years of hands-on experience in developing and deploying machine learning models
• Ability to write scalable production-quality code
• Proficiency in classical machine learning methods and familiarity with newer techniques like LLMs
• Excellent programming skills in Python, Java, or similar languages
• Experience with machine learning frameworks such as TensorFlow, PyTorch, Hugging Face, Keras, MXNet, or scikit-learn
• Familiarity with search/information retrieval, and ranking systems
• Strong communication skills and ability to work collaboratively
• Analytically minded with a focus on metrics and evaluation
• Motivation to work hard and always be learning

Desirable

• We are seeking a passionate and skilled Machine Learning Engineer to join our effort to push the frontiers of risk management
• This role offers the opportunity to work with cutting-edge Large Language Models (LLMs), utilizing techniques like Retrieval-Augmented Generation (RAG), Few-Shot Learning, Prompt Engineering, Fine-Tuning, Semantic Search, and Knowledge Distillation, etc
• You will apply your expertise to build advanced AI/ML solutions, enhancing our AuditBoard product portfolio with features like chat systems, agentic workflows, intelligent data extraction, and personalized insights
• If you're excited about leveraging modern AI/ML techniques to transform the industry, this role is for you
• Join our customer-focused team dedicated to continuous learning and innovation
• Build, ship, and own product features end-to-end
• Work with designers, and product managers to create high-performing product features
• Apply a range of techniques—from classical ML to LLM-based approaches (RAG, prompt engineering, fine-tuning, semantic search)—with a strong focus on reliability, performance, and maintainability
• Write well-designed, maintainable, and testable code
• Write clear and well-defined design documentation
• Troubleshoot, debug, and resolve software bugs
• Be product-minded and think about the customer
• Stay updated on AI/ML advancements and explore new techniques and tools
• Participate in an Agile software development life cycle
• Work with Python, JavaScript, Node.JS, Docker, PostgreSQL, Kubernetes, etc