About the Company

Clarifai is a leading, full-lifecycle deep learning AI platform for computer vision, natural language processing, LLM's and audio recognition. We help organizations transform unstructured images, video, text, and audio data into structured data at a significantly faster and more accurate rate than humans would be able to do on their own. Founded in 2013 by Matt Zeiler, Ph.D. Clarifai has been a market leader in AI since winning the top five places in image classification at the 2013 ImageNet Challenge. Clarifai continues to grow with employees remotely based throughout the United States, Canada, Argentina, India and Estonia.

We have raised $100M in funding to date, with $60M coming from our most recent Series C, and are backed by industry leaders like Menlo Ventures, Union Square Ventures, Lux Capital, New Enterprise Associates, LDV Capital, Corazon Capital, Google Ventures, NVIDIA, Qualcomm and Osage.

Clarifai is proud to be an equal opportunity workplace dedicated to pursuing, hiring, and retaining a diverse workforce.

Your Impact

You will be essential in contributing to our core ML infrastructure, helping researchers and users to train and serve state of the art models to our customers!

The Opportunity

• Work with research teams to design and build our training infrastructure
• Prototype new training frameworks and production-ize solutions at scale
• Design, optimize and test model integration infrastructure
• Work with data team to implement ETL/ELT pipeline

Requirements

• 5-8+ years of experience developing Machine learning infrastructure
• Familiarity with setting up ML lifecycle systems
• Comfortable working with open source software
• Hands-on experience implementing production machine learning systems at scale

Great to Have

• Prior experience with with Tensorflow, PyTorch, Onnx, Nvidia Triton, kubeflow is a plus
• Experience with Golang, Relational DB
• Experience with async processing

The salary hiring range for this position is $150,000 - $200,000 and flexible depending on relevant experience.