Baselayer is built by financial institutions, for financial institutions. Started in 2023 by experienced founders, Baselayer works with banks, Fortune 500 tech cos, fintechs, and AI experts to revolutionize fraud prevention and compliance. Baselayer has raised funding and earned notable ARR as part of its growth narrative.

About You You want to learn from the best of the best, get your hands dirty, and put in the work to hit your full potential. You’re aiming to be an impeccable 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’re comfortable working with large-scale data and enjoy optimizing performance for computationally intensive ML systems

You have a strong foundation in AI/ML fundamentals, particularly with LLMs, and are eager to experiment with emerging techniques

You prioritize responsible AI practices and model governance, especially in regulated environments like KYC/KYB

You have a keen eye for detail and take pride in writing clean, maintainable code while optimizing for model performance

You thrive in a high-trust, ownership-focused environment and are comfortable working across different levels of abstraction

You are a problem-solver who navigates the unknown confidently

You are a proactive self-starter who thrives in dynamic settings

You are highly intelligent and clever, with pride in your models

You are highly feedback-oriented and value candor to reach the next level

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 with large-scale, high-dimensional data

Advanced ML Techniques: Implement and experiment with state-of-the-art techniques including RLHF and parameter-efficient fine-tuning methods (e.g., LoRA) to improve LLMs for identity-related use cases

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 regulatory compliance (KYC/KYB)

Performance Optimization: Optimize model inference and training for efficient processing of identity data while maintaining reliability

Experimentation & Evaluation: Design and conduct experiments to evaluate model performance, debug issues, and monitor ML services, while improving architectures for diverse data and use cases

Hybrid in SF. In-office 3 days/week

Flexible PTO

Collaborate with a smart, genuine, ambitious team

Salary & Benefits 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

San Francisco, CA – location details omitted here for refinement; original postings have been removed to keep the description concise and job-focused.

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