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Backend Engineering Intern

| Greater NYC Area

About Clarifai

Clarifai is an artificial intelligence company that excels in visual recognition, solving real-world problems for businesses and developers alike. Founded in 2013 by Matthew Zeiler, a foremost expert in machine learning, Clarifai has been a market leader since winning the top five places in image classification at the ImageNet 2013 competition and predicting more than 1.2 billion concepts in photos and videos every month. Clarifai’s powerful image and video recognition technology is built on the most advanced machine learning models and made easily accessible by a clean API, empowering developers all over the world to build a new generation of intelligent applications.

Clarifai raised a $30 million Series B in 2016 led by Menlo Ventures, Union Square Ventures, and Lux Capital. Existing investors include Google Ventures, Qualcomm Ventures, NVIDIA Ventures, Corazon Capital, LDV Capital, Osage University Partners, and New York University.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.


Are you interested in building our AI systems with some of the best engineers in the world?

As a Backend Engineering Intern at Clarifai, you will assist our engineering teams by improving features, reliability, flexibility, and scalability as usage increases.

In this role, you will build in Python and Go. You will also have the opportunity to participate in the software design. You will have an immediate impact on the advancement of our products, while supplying your own ideas in building new features.


  • In order to be considered, you'll need a BS, MS, or a PhD Degree in Computer Science or a related background.
  • We will also strongly prefer that you are a third year undergrad or higher
  • You can start your internship in May at our New York City office
  • You have ability to learn, handle uncertainty, self-disciplined, and have phenomenal verbal and written communication


  • Get familiar with our code base (as well as the backend and infrastructure teams).
  • Get adjusted to working with what we’ve built and who has helped and give us the feedback only a fresh perspective can bring.
  • Learn about the distinctive challenges of machine learning systems using GPUs.
  • Identify and resolve production bugs.
  • Assist in planning feature development, requirements, and our technical road map.
  • Accelerate development of our machine learning API feature set.
  • Improve user management and refining API permissions
  • Build and measure benchmarking and stress test tools.
  • Measure and optimize of the customer facing custom training API service.
  • Design, deploy and run web-scale distributed storage systems of various flavors, both relational (MySQL, Postgres) and NoSQL (Redis, Elasticsearch, etc.).
  • Expand on quality assurance infrastructure and continuous deployment.
  • Identify web security risks and write tools to improve security issues.
  • Work closely and communicate with product managers on hiring and timelines.
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