Machine Learning Engineer Co-Op (Data Labeller)

• Posted 10 days ago • Updated 10 days ago
Full Time
On-site
USD $22.00 - 30.00 per hour
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Critical Thinking
  • Product Design
  • Large Language Models (LLMs)
  • Sales
  • Elasticsearch
  • Workflow
  • Computer Vision
  • Computer Science
  • Data Structure
  • Algorithms
  • Linear Algebra
  • Artificial Intelligence
  • Python
  • Data Analysis
  • Probability
  • Machine Learning (ML)
  • Linux
  • Forms
  • Honesty
  • Finance
  • Evaluation
  • Recruiting
  • Value Engineering
  • Messaging

Summary

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 seeking an enthusiastic Machine Learning Co-ops to join our team, focusing on our Computer Vision and Agentic AI projects. Ideal candidates should be keen to explore the intricacies of the auto loan industry and will learn about large-scale data annotation, cleaning and product design for real-world applications of Large Language Models (LLMs) and automated verifications.

Key Responsibilities

  • Annotate documents data from sales-dealers and customers to train AI workflows
  • Develop and refine prompts and Retrieval-Augmented Generation (RAG) technique cvg cant es to enhance the performance of CV models and AI workflows
  • Assess the needs of dealers and customers, and implement AI verification functionalities to address those needs
  • Fine-tune Computer Vision models as time permits and based on the availability of annotated data

Requirements

  • Bachelor's degree in Computer Science or a related field
  • M.S. in Computer Science or a related field preferred
  • Coursework or experience in Data Structures, Algorithms, Linear Algebra, Probability, and foundational Machine Learning and Artificial Intelligence concepts
  • Familiarity with Python and its data analysis libraries
  • Strong grasp of core CS and ML concepts (Interview process will include questions on coursework, coding, probability, machine learning, and Linux fundamentals)

$22 - $30 an hour

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!

Background Checks

After an offer is accepted, Lendbuzz conducts a pre-employment background check. Any evaluation of the background check will be subject to an individualized assessment, taking into account the applicant's or employee's specific record and the responsibilities and requirements of the particular role.

A Note on Recruiting Outreach

We've been made aware of individuals falsely claiming to represent Lendbuzz using lookalike email addresses (eg @lendbuzzcareers.com). Please note that all legitimate emails from our team come from @lendbuzz.com. We will never ask for sensitive information or conduct interviews via messaging apps.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90922487
  • Position Id: 24372613
  • Posted 10 days ago
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