Machine Learning Product Summer Intern

Posted Yesterday
Easy Apply
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Hiring Remotely in US
Remote
20-20 Hourly
Internship
eCommerce
The Role
Intern will collaborate with data scientists and ML engineers to develop machine learning models and improve data pipelines for retail media insights.
Summary Generated by Built In

Machine Learning Product Summer Intern

Overview 

Join Pacvue’s Data, ML and AI organization to help build intelligent systems that power automation, optimization, and insights across retail media and commerce. This role will contribute to applied machine learning and data initiatives that directly support product capabilities used by thousands of brands and agencies worldwide. 

Project Scope 

  • Work with Pacvue’s Data, ML and AI team to support the development and experimentation of machine learning models that improve campaign optimization, forecasting, or decision automation. 
  • Collaborate with data scientists, ML engineers, and product managers to explore large-scale retail media datasets and identify patterns that can inform product capabilities. 
  • Assist in building or improving data pipelines, feature engineering processes, or model evaluation frameworks. 
  • Participate in prototyping AI-enabled product features such as recommendations, automation workflows, or predictive insights. 
  • Contribute to technical documentation and communicate findings with engineering and product stakeholders. 

Deliverables / Milestones 

  • Develop and evaluate at least one machine learning model or analytical prototype using Pacvue datasets. 
  • Produce exploratory data analysis and insights that support model development or product decisions. 
  • Deliver a working prototype, experiment report, or pipeline improvement demonstrating measurable impact or learning. 
  • Present project outcomes and recommendations to the Data, ML and AI team and relevant product stakeholders at the end of the internship. 
  • Document code, methods, and results to enable future productionization or further experimentation. 

Learning Objectives 

  • Gain hands-on experience applying machine learning techniques to large-scale real-world commerce and retail media datasets. 
  • Learn how data, ML models, and AI capabilities are integrated into production SaaS platforms. 
  • Develop practical skills in Python-based data analysis and machine learning tools such as Pandas, SQL, and ML frameworks. 
  • Build experience collaborating in a cross-functional environment with engineering, data science, and product teams. 
  • Improve the ability to translate technical analysis into insights that influence product and business decisions. 

Skills & Qualifications

  • Interest in machine learning, data, or AI-driven products
  • Familiarity with programming languages (e.g., Python preferred)
  • Basic data analysis skills (Excel, SQL, or similar tools)
  • Analytical and problem-solving mindset
  • Ability to communicate technical concepts clearly
  • Curious, proactive, and eager to learn

Location/Time Zone Preference: United States - Central, Mountain, or Pacific Time Zones

This is an hourly, remote summer internship for college students, offering up to 35 hours per week at a rate of $20 per hour.
This role is available for our 9-week summer cohort running from May 18 – July 17.


#LI-Remote

Pacvue is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability.

Top Skills

Pandas
Python
SQL
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The Company
HQ: Los Angeles, California
434 Employees

What We Do

Pacvue is a commerce acceleration platform that empowers businesses to discover the most impactful opportunities, activate sales growth, and streamline daily operations. The platform turns insights into actionable recommendations by integrating retail media, commerce management, and measurement. With Pacvue as your guide, you can see further, think bigger, and move faster through your commerce journey

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