Machine Learning Engineer

Baselayer is an intelligent business identity platform trusted by over 2,200 financial institutions, focusing on verifying businesses and automating KYB processes. They are seeking a Machine Learning Engineer to develop and integrate ML models, design ML systems, and ensure compliance with industry standards while optimizing performance for large-scale data. Responsibilities Build and maintain ML models and integrate them with various data sources, ensuring scalability, high performance, and adaptability for autonomous agents in the GTM space Architect and design core ML services that support KYC/KYB processes, leveraging knowledge graphs and LLMs for dynamic use cases Develop and maintain robust data pipelines for feature extraction and transformation, focusing on scalability and performance when handling large-scale, high-dimensional data Implement and experiment with state-of-the-art techniques including reinforcement learning from human feedback (RLHF) and parameter-efficient fine-tuning methods (e.g., LoRA) to improve LLMs for specific use cases within the identity space Build and maintain infrastructure for model training, evaluation, and deployment, creating a scalable platform foundation for continued innovation Ensure ML systems meet industry standards for fairness, explainability, and compliance, particularly around KYC/KYB regulations Implement optimizations for model inference and training, ensuring ML services can efficiently process identity data while maintaining reliability Design and conduct experiments to evaluate model performance, debug issues, and monitor ML services, while continuously improving architectures to handle diverse data and use cases Skills 1-3 years of experience in machine learning development, working with Python and building ML models Comfortable working with large-scale data and enjoy optimizing performance for computationally intensive ML systems Strong foundation in AI/ML fundamentals, particularly with LLMs, and eager to experiment with emerging techniques Prioritize responsible AI practices and model governance, especially in regulated environments like KYC/KYB Keen eye for detail and take pride in writing clean, maintainable code while optimizing for model performance Thrive in a high-trust, ownership-focused environment and are comfortable working across different levels of abstraction Problem-solver who navigates the unknown confidently Proactive self-starter who thrives in dynamic settings Incredibly intelligent and clever. You take pride in your models Highly feedback-oriented. We believe in radical candor and using feedback to get to the next level Benefits Hybrid in SF. In office 3 days/week Flexible PTO Healthcare, 401K Smart, genuine, ambitious team Company Overview We create innovative technology to transform the data center. We deliver hardware and software products which ensure the data center. It was founded in 2008, and is headquartered in Chandler, Arizona, USA, with a workforce of 51-200 employees. Its website is