Baselayer
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
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