Head of Quality Engineering

About the Company:

Clarifai is a leading, full-lifecycle deep-learning AI platform for computer vision, natural language processing, audio recognition, and large language models (LLM). 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. We 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.

The Opportunity:

• Work with and lead Clarifai’s quality engineering function defining and implementing the overall quality strategy to ensure product reliability and performance. 
• Work closely with engineering, product, and operations teams to integrate quality processes throughout the product lifecycle. 
• Drive the development and adoption of test automation tools and frameworks to improve efficiency and coverage. 
• Establish and monitor key quality metrics to track and improve product quality.

Impact:

Make the highest quality enterprise AI tools available to customers globally while fostering a culture of quality across all Clarifai employees

Requirements:

• 8+ years of experience in quality engineering, with at least 3 years in a leadership role across a number of technologies, including Python, Javascript (React)
• Advanced programming and automation skills to write and maintain test scripts and automation frameworks
• Expert knowledge of testing methodologies (e.g., unit testing, integration testing, system testing, acceptance testing), including manual methods 
• Carry out QA activities as a ‘player-coach’, including analyzing bugs during tests, creating tests to identify problems, and communicating patch fixes.
• Advanced experience with popular automation frameworks like Cucumber, Selenium, Cypress, Playwright.

Nice to Have:

• Deep understanding of AI technologies, machine learning models, and data-driven systems.
• Software development expertise in Golang or other object oriented languages.