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 Engineer who is passionate about delivering impactful solutions and moving models from research environments into high-performance production systems. The ideal candidate will possess a strong background in software development principles, exceptional coding skills, and a working understanding of machine learning and DevOps methodologies.
Key Responsibilities:
Collaborate closely with data scientists and cross-functional teams to integrate machine learning models seamlessly into production systemsImplement end-to-end solutions, including architecture design, business logic, deployment and monitoringPerform exploratory data analysis, build baseline models and fine-tune existing architectures to support the data science teamPackage, containerize, and deploy ML models (Financial, Text, Image) as scalable microservices (using FastAPI, Docker)Stay updated with advancements in machine learning and related technologies to continuously improve our solutionsDrive the adoption of rigorous engineering standards and testing practices for ML codebases, ensuring high-quality, reliable ML model releases
Key Requirements:
Master's or Bachelor's degree in Computer Science, Engineering, or a related field with 2+ years of relevant industry experienceStrong understanding of computer science fundamentals, object-oriented programming and software design patternsStrong knowledge of machine learning fundamentals and proficiency in data analysisProficiency in Python, SQL, FastAPI or other RESTful API architectures and AWSFamiliarity with numpy, pandas, torch, scikit-learn and other Python libraries commonly used in machine learning
