Machine Learning Engineer

Trusted by 2,200+ financial institutions, Baselayer is the intelligent business identity platform that helps verify any business, automate KYB, and monitor real-time risk. Baselayer’s B2B risk solutions & identity graph network leverage state & federal government filings and proprietary data sources to prevent fraud, accelerate onboarding, and lower credit losses.

Introduction

Baselayer, a trusted intelligent business identity platform for over 2,200 financial institutions, is seeking an impeccable Machine Learning Engineer. We are looking for an individual who is eager to learn from and work alongside the best, with a strong desire to hit their full potential by building cutting-edge AI solutions.

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.
• Experimentation & Evaluation: 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.

Requirements

• 4-8 years of experience in machine learning development, working with Python and building ML models.
• Comfortable working with large-scale data and 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, taking pride in writing clean, maintainable code while optimizing for model performance.
• Thrive in a high-trust, ownership-focused environment and 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; takes pride in their models.
• Highly feedback-oriented; believes in radical candor and using feedback to get to the next level.

Benefits

• Equity package.
• Unlimited vacation.
• Fully paid health insurance, dental, and vision.
• 401(k) with company match.

About Company

Trusted by 2,200+ financial institutions, Baselayer is the intelligent business identity platform that helps verify any business, automate KYB, and monitor real-time risk. Baselayer’s B2B risk solutions & identity graph network leverage state & federal government filings and proprietary data sources to prevent fraud, accelerate onboarding, and lower credit losses.