Baselayer is looking to solve the problem of verifying any business, automating KYB, and monitoring real-time risk for 2,200+ financial institutions
Requirements
- 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 are 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
- Experience with reinforcement learning from human feedback (RLHF) and parameter-efficient fine-tuning methods (e.g., LoRA)
- Knowledge of knowledge graphs and LLMs for dynamic use cases
Responsibilities
- Model Development & Integration: 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
- ML System Design: Architect and design core ML services that support KYC/KYB processes, leveraging knowledge graphs and LLMs for dynamic use cases
- Data Processing & Feature Engineering: Develop and maintain robust data pipelines for feature extraction and transformation, focusing on scalability and performance when handling large-scale, high-dimensional data
- Advanced ML Techniques: 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
- ML Infrastructure: Build and maintain infrastructure for model training, evaluation, and deployment, creating a scalable platform foundation for continued innovation
- Model Governance & Compliance: Ensure ML systems meet industry standards for fairness, explainability, and compliance, particularly around KYC/KYB regulations
- Performance Optimization: Implement optimizations for model inference and training, ensuring ML services can efficiently process identity data while maintaining reliability
Other
- Hybrid in SF. In office 3 days/week
- Flexible PTO
- Healthcare, 401K
- Smart, genuine, ambitious team
- Problem-solver who navigates the unknown confidently
