With experience across far-ranging banks, Fortune 500 tech companies, fintech unicorns, and AI experts, Baselayer is built by financial institutions, for financial institutions. Started in 2023 by experienced founders Jonathan Awad and Timothy Hyde, Baselayer has raised $20 million and hit $2 million in ARR faster than any other identity company in history. Today, more than 2,000 financial institutions and government agencies are customers, and Baselayer is revolutionizing fraud prevention and compliance. About You: You want to learn from the best, get hands-on experience, and work hard to reach your full potential. You're motivated by a desire to excel and want to be an exceptional machine learning engineer working on cutting-edge AI solutions. 1-3 years of experience in machine learning development, with Python and ML models Comfortable working with large-scale data and optimizing performance of ML systems Strong foundation in AI/ML fundamentals, especially with LLMs, and eager to experiment with new techniques Prioritize responsible AI practices and model governance, especially in regulated environments like KYC/KYB Keen eye for detail, writing clean, maintainable code, and optimizing model performance Thrives in a high-trust, ownership-focused environment, comfortable across different levels of abstraction Problem-solver confident navigating unknowns Proactive self-starter in dynamic settings Highly intelligent and clever, takes pride in models Receptive to feedback and committed to continuous improvement Responsibilities: Build and maintain scalable ML models, integrating with data sources for autonomous agents in GTM Design core ML services supporting KYC/KYB, leveraging knowledge graphs and LLMs Develop data pipelines for feature extraction and transformation, focusing on scalability Experiment with advanced techniques like RLHF and LoRA to enhance LLMs for identity use cases Build and maintain ML infrastructure for training, evaluation, and deployment Ensure ML systems meet standards for fairness, explainability, and compliance, especially KYC/KYB Optimize model inference and training for efficiency and reliability Design experiments to evaluate and improve models, monitor ML services Hybrid work in SF, 3 days/week in office Flexible PTO, collaborative and ambitious team Salary Range: $150k – $225k + Equity (0.05% – 0.25%) Seniority level Entry level Employment type Full-time Job function Engineering and Information Technology Industries Technology, Information and Internet #J-18808-Ljbffr Baselayer
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