Job Description

Position Title: Junior ML Engineer
Location: Miami, Florida (In-Office)
Reports To: Director of Technology
Position Type: Permanent – Full-Time

ABOUT US

duPont REGISTRY Group proudly marks four decades as a cornerstone of the luxury automotive market in 2025. Renowned for connecting millions of buyers and sellers worldwide, duPont REGISTRY Group has facilitated billions in automotive transactions while setting the standard for excellence in the industry.

POSITION OVERVIEW
As a Junior Machine Learning Engineer, you will assist in the development and deployment of machine learning models that enhance customer experience and optimize inventory management. Working closely with senior engineers and data scientists, you will gain hands-on experience with real-world datasets and state-of-the-art ML techniques while contributing to projects that drive the success of our luxury automotive platform.

KEY RESPONSIBILITIES

• Assist in building and testing machine learning models for vehicle recommendations, pricing, demand forecasting, and customer segmentation.


• Support data cleaning, preprocessing, and feature engineering efforts to prepare data for modeling.


• Collaborate with data engineering and software teams to help integrate ML models into production systems.


• Help monitor model performance and assist in tuning and improving algorithms.


• Participate in research on new ML techniques and tools under guidance.


• Contribute to documentation and maintain code quality standards.


• Learn and adhere to data privacy regulations and best practices.


• Work closely with senior team members to align ML work with business goals.

QUALIFICATIONS

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.


• Some experience or coursework in machine learning, data science, or related areas.


• Familiarity with ML libraries such as TensorFlow, PyTorch, or Scikit-learn is a plus.


• Basic programming skills in Python and SQL; knowledge of other languages is beneficial.


• Understanding of fundamental ML concepts including supervised and unsupervised learning.


• Eagerness to learn, strong analytical skills, and attention to detail.


• Good communication skills and ability to work collaboratively in a team environment.

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