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 computer vision, Clarifai has been a market leader since winning the top five places in image classification at the ImageNet 2013 competition. Clarifai’s powerful image and video recognition technology is built on the most advanced machine learning systems and made easily accessible by a clean API, empowering developers and businesses all over the world to build a new generation of intelligent applications.
We’ve secured a $10M Series A round of funding, led by Google Ventures, NVIDIA, Qualcomm, and Union Square Ventures, and to continue to succeed, we need people like you to join the team here in NYC!
- You want to help break new ground on emerging problems as we explore how research can be applied to new areas.
- You are interested in building incredible applications and tools.
Improve performance of convolutional neural networks.
- Develop NLP / semantic word models for text understanding, entity extraction, and classification.
- Work to understand image, video, and audio.
- Engineer and code in the real-world, not just in class.
- Optimize and benchmark algorithms.
- Do machine learning research and publishing papers after rigorous evaluation.
- Handle internet-scale data sets and the unique problems that they pose.
- Program in the GP-GPU model, e.g Cuda or openCL.
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.
By signing the White House’s Tech Inclusion pledge, we at Clarifai agree to implement and publish company-specific goals to recruit, retain, and advance diverse technology talent, and operationalize concrete measures to build and sustain an inclusive culture; and invest in partnerships to build a diverse pipeline of technology talent to increase our ability to recognize, develop and support talent from all backgrounds.