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

Baselaer is seeking an impeccable Machine Learning Engineer to contribute to cutting-edge AI solutions. Trusted by over 2,200 financial institutions, Baselayer provides an intelligent business identity platform that verifies businesses, automates KYB, and monitors real-time risk. This role involves working with state and federal government filings and proprietary data sources to prevent fraud, accelerate onboarding, and reduce credit losses.

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 and 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, taking pride in your models.
• Highly feedback-oriented, embracing radical candor to reach 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.

How to Apply

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