Job Description

About Baselayer With experience across diverse banks, Fortune 500 tech companies, fintech unicorns, and AI experts, Baselayer is built by financial institutions, for financial institutions. Founded in 2023 by seasoned entrepreneurs Jonathan Awad and Timothy Hyde, Baselayer has raised $20 million and achieved $2 million in ARR faster than any other identity company in history. Today, over 2,000 financial institutions and government agencies are our customers, and we are revolutionizing fraud prevention and compliance. Check out their press release here → About You You want to learn from the best, get hands-on experience, and work hard to reach your full potential. You're motivated not just by success but by proving yourself and striving for excellence. You aim to be an exceptional machine learning engineer working on cutting-edge AI solutions. You have 1-3 years of experience in machine learning development, working with Python and building ML models. You are comfortable working with large-scale data and enjoy optimizing performance for computationally intensive ML systems. You possess a strong foundation in AI/ML fundamentals, especially with LLMs, and are eager to experiment with emerging techniques. You prioritize responsible AI practices and model governance, particularly in regulated environments like KYC/KYB. You have a keen eye for detail, pride in writing clean, maintainable code, and focus on model performance. You thrive in a high-trust, ownership-driven environment and are comfortable working across different levels of abstraction. You are a problem-solver confident in navigating the unknown. You are a proactive self-starter who thrives in dynamic settings. You are highly intelligent, clever, and take pride in your models. You are feedback-oriented, embracing radical candor to improve continuously. Responsibilities Model Development & Integration: Build and maintain ML models, integrating them with various data sources to ensure scalability, high performance, and adaptability for autonomous agents in the GTM space. ML System Design: Architect core ML services supporting KYC/KYB processes, leveraging knowledge graphs and LLMs for dynamic use cases. Data Processing & Feature Engineering: Develop robust data pipelines for feature extraction and transformation, focusing on scalability when handling large, high-dimensional data. Advanced ML Techniques: Implement state-of-the-art techniques like RLHF and LoRA to enhance LLMs for identity-related use cases. ML Infrastructure: Build and maintain infrastructure for training, evaluation, and deployment, creating a scalable platform for ongoing innovation. Model Governance & Compliance: Ensure ML systems meet standards for fairness, explainability, and regulatory compliance. Performance Optimization: Optimize model inference and training for efficient processing and reliability. Experimentation & Evaluation: Conduct experiments to evaluate and improve model performance, debug issues, and monitor ML services. Benefits Hybrid work in SF, 3 days/week in office Flexible PTO Healthcare, 401K Smart, genuine, ambitious team Start date: June Salary Range: $150k – $225k + Equity (0.05% – 0.25%) Additional Details Seniority Level: Entry level Employment Type: Full-time Job Function: Engineering and Information Technology Industries: Technology, Information, Internet #J-18808-Ljbffr Baselayer

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