Machine Learning Engineer (Boston)

Sorry, this job was removed at 09:53 a.m. (CST) on Tuesday, Mar 25, 2025
Boston, MA
Hybrid
Artificial Intelligence • Big Data • Machine Learning • Analytics • Financial Services
The Role

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’re looking for a Machine Learning Engineer who excels in building and maintaining robust systems that deliver real value to users. You’re skilled at turning functional logic into scalable code and integrating systems across teams. You embrace continuous learning, stay updated on new technologies, and drive process improvements.


At Lendbuzz, you’ll work closely with infrastructure teams to design and deploy end-to-end pipelines, collaborate on ML model integration, and ensure high-quality releases. You take pride in your craft and push the team to maintain high standards in both development and testing.

Key Responsibilities:

  • Build machine learning and deep learning models based on financial and other modalities like images and text
  • Devise new research methods to solve bleeding edge problems and get a chance to work on publishable outcome
  • Conduct in-depth analysis of machine learning models and pioneer research methodologies to address cutting-edge challenges
  • Collaborate closely with cross-functional teams to integrate machine learning models seamlessly into production systems
  • Design and develop robust, ML pipelines and systems
  • 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
  • Stay updated with advancements in machine learning and related technologies to continuously improve our solutions

Requirements:

  • Masters (M.S.) with 3+ years of full time experience in industry
  • Strong knowledge in Computer Vision, Deep Learning, Linear Algebra, Probability, Data Structures and Algorithms
  • Strong knowledge of numpy, scipy, pandas, torch, scikit-learn and other Python libraries commonly used in machine learning is a must
  • Strong grasp of CS and ML foundation and core concepts
  • Experience designing and implementing APIs
  • Intimate familiarity with Python, PostgreSQL, FLASK, REST and Linux
  • Able to convert functional logic into code is a must
  • Fluency on the Linux command-line, including utilities (grep, find, etc.) and use of git

We believe:


Diversity is a competitive advantage. We celebrate our differences, and are better when we have a variety of experiences, viewpoints, and backgrounds.


Compassion is a strength. We care about our customers and look to build long-term relationships with them.


Simplicity is a key feature. We work hard to make our forms and processes as painless and intuitive as possible.


Honesty and transparency are non negotiable. We incorporate these traits in all of our interactions.


Financial opportunity belongs to everyone. We work every day to improve lives by extending this opportunity.


If you believe these things too then we would love to hear from you!

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The Company
HQ: Boston, MA
148 Employees
Year Founded: 2018

What We Do

Lendbuzz is an AI-based auto finance platform that helps consumers with thin or no credit history obtain financing when purchasing a car. Powered by machine learning and proprietary algorithms, Lendbuzz can assess the creditworthiness of consumers with limited credit history—a group underserved by traditional banks. Through their auto dealership partners, Lendbuzz offers consumers attractive financing solutions while opening up opportunities for those dealerships to serve a more diversified client base. Lendbuzz is headquartered in Boston, Massachusetts and was founded in 2015.

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