Machine Learning Research Scientist

At Lendbuzz, we believe financial opportunity should be more personalized and fair. We develop innovative technologies that provide underserved and overlooked borrowers with better access to credit. From our employees to our dealers, partners, and borrowers, we’ve built a company and a culture around a resolute belief in the promise and power of diversity. We value independent and critical thinking. We are looking for a talented Machine Learning Research Scientist who is passionate about delivering impactful solutions and thrives in a dynamic, collaborative environment. The ideal candidate will possess a strong background in software development principles, exceptional coding skills, and a deep understanding of deep learning based Computer Vision.

Responsibilities:

• Build ConvNet/Transformer models on structured loan document images such as ID doc, passport, title, insurance binder and bank statements to extract useful information for automatic approval of loans.
• Collaborate closely with cross-functional teams to integrate machine learning models seamlessly into production systems.
• Design and develop robust, scalable pipelines and systems using software engineering best practices.
• Implement end-to-end solutions, including architecture design, business logic, and deployment.
• Drive the adoption of rigorous testing practices, ensuring high-quality, reliable ML model releases.
• Devise new research methods to solve bleeding edge problems and get a chance to work on publishable outcomes.
• Conduct in-depth analysis of machine learning models and pioneer research methodologies to address cutting-edge challenges.
• Stay updated with advancements in machine learning and related technologies to continuously improve our solutions.

Requirements:

• Ph.D in Computer Science, Engineering, or a related field with 3+ years of relevant industry experience.
• Solid grasp of computer science fundamentals and core concepts in machine learning.
• Strong knowledge of numpy, scipy, pandas, torch, scikit-learn and other Python libraries commonly used in machine learning is a must.
• Strong knowledge in Deep Learning, Linear Algebra, Probability, Data Structures and Algorithms.
• Proficiency in Python for data manipulation, PostgreSQL for database management, and Flask for web development.
• Strong understanding of object-oriented programming principles and software design patterns.