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
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