Intern, Machine Learning

Posted 6 Hours Ago
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New York, NY
Internship
AdTech
The Role
As a Machine Learning Intern, you will work with engineers and data scientists to develop and optimize machine learning models for advertising technology. Key responsibilities include coding, assisting model deployment, and debugging issues. You will gain hands-on experience in the Machine Learning Development Lifecycle (MLDLC) within an Agile environment.
Summary Generated by Built In

Kargo creates breakthrough cross-screen ad experiences for the world’s leading brands and publishers. Every day, our 600+ employees bring the power of their creativity and diversity to radically raise the bar on what mobile, CTV, AI, social, and eCommerce can do to wow consumers and build businesses. Now 20 years strong, Kargo has offices in NYC, Chicago, Austin, LA, Dallas, Sydney, Auckland, London and Waterford, Ireland. Humble brag: In 2024, Kargo was recognized as a Best Place to Work by Ad Age and Built In.

Who We Hire

Success takes all kinds. Diversity describes our workforce. Inclusion defines our culture. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, marital status, age, national origin, protected veteran status, disability or other legally protected status. Individuals with disabilities are provided reasonable accommodation to participate in the job application process, perform essential job functions, and receive other benefits and privileges of employment. 

Title: Intern, Machine Learning

Job Type: Internship, 3 Days In Office
Job Location: New York, NY

Compensation: $20.00/ hour
Duration: June 2, 2025 - August 8, 2025 (10 weeks)

The Opportunity

As a Machine Learning Intern at Kargo, you will be part of a team of engineers and data scientists working to develop and optimize machine learning models that power Kargo’s advertising technology. Your work will directly contribute to maximizing revenue for publishers and enhancing brand value for marketers by leveraging AI-driven insights. 

You will gain first-hand experience in the Machine Learning Development Lifecycle (MLDLC) while working within an Agile (Scrum) environment. You will have the opportunity to engage in diverse areas, including model development, data engineering, MLOps, and deployment, using industry-leading technologies such as Python, TensorFlow/PyTorch, Kubernetes, Docker, AWS, and more.

The Daily To-Do

  • Design and develop production-grade code that adheres to Kargo’s code standard
  • Support data science and machine learning teams with model development and deployment
  • Compose documentation to improve knowledge sharing and onboarding process
  • Assist Tech Ops in diagnosing and debugging production issues

Qualifications

  • Currently enrolled in a Bachelor's or Master's degree program in Computer Science or related technical field
  • Familiarity with machine learning and programming languages like Python/R 
  • Proactive and has a passion for problem-solving with the audacity to take on unknown challenges
  • Solid understanding of algorithms and data structures
  • Experience with RDBMS and comfortable writing SQL queries
  • Experience working with a modern frontend framework like Angular, React, or Vue

Follow Our Lead

  • Big Picture:  kargo.com
  • The Latest:  Instagram (@kargomobile) and LinkedIn (Kargo)

Top Skills

Python
R
The Company
HQ: New York, NY
620 Employees
Hybrid Workplace
Year Founded: 2003

What We Do

Kargo creates breakthrough cross-screen ad experiences for the world’s leading brands and publishers. Every day, our 600+ employees bring the power of their creativity and diversity to radically raising the bar on what mobile, CTV, AI, social, and eCommerce can do to wow consumers and build businesses. Now 20 years strong, Kargo has offices in NYC, Chicago, Austin, LA, Dallas, Sydney, Auckland, London and Waterford, Ireland. Humble brag: In 2024, Kargo was recognized as a Best Place to Work by Built In.

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Kargo Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: 3 days a week
HQNew York, NY
Chicago, IL
Santa Monica, CA
Waterford, Ireland
Learn more

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