ML Community Ops Engineer

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:

As an ML Community Ops Engineer you will grow Clarifai’s brand by adding the latest state of the art AI to Clarifai’s community. You will be in touch with advancements in AI, and ensure the latest models can be used by Clarifai users. You will work with Marketing to market new models that are added to our platform. In doing this you will expose the Clarifai brand to a broader community.

Your Opportunity:

• Be an expert in publicly available open source models that have a high score / popularity / buzz potential and import them into Clarifai community
• Continuously import the top models to Clarifai’s community, test models in various scenarios
• Craft compelling language that targets technical and non-technical users, add unique examples for previews before publishing content
• Support marketing in promoting newly added models
• Engage with community to maximize backlinking from original authors 
• Build custom python demos for some of the models

Your Experience:

• Experience with machine learning model development and evaluation: the candidate should have experience in developing and training machine learning models. They should understand different model architectures, regularization techniques, and evaluation metrics. 
• Deep learning expertise: familiarity with deep learning architectures, such as convolutional neural networks (CNNs) or recurrent neural networks (RNNs). 
• Follow the machine learning community closely: the candidate should follow the developments in AI space closely and stay up to date on a daily basis.
• Strong understanding of machine learning concepts, principles and algorithms: the candidate should be experienced with libraries like TensorFlow, PyTorch and scikit-learn.
• Advanced programming skills in Python: the candidate should be able to write efficient and scalable code, as well as perform data manipulation and preprocessing tasks.
• Knowledge of ML frameworks and tools: the candidate should have experience with popular ML frameworks and tools, such as TensorFlow, PyTorch, Keras or Triton Inference Server. They should be comfortable with training models, deploying them into production, and optimizing their performance.
• Understanding of cloud platforms: the candidate should be familiar with cloud platforms like AWS, Azure, or Google Cloud is often required. They should understand how to leverage cloud resources for scalable and distributed computing, as well as deploying and managing ML models on these platforms.
• Data processing and analysis: the candidate should have experience with data processing and analysis techniques, including data cleaning, feature engineering, and exploratory data analysis. They should be able to work with large datasets.
• Software engineering skills: the candidate should possess strong software engineering skills to build robust and scalable ML systems. This includes knowledge of software development principles, version control systems like Git, and familiarity with software engineering best practices like code documentation and testing.

Preferred Experience:

• You stay on top of the latest generative AI technologies and are excited to build content around them
• Passionate about opens source development and interested in contributing to Clarifai’s open-source projects
• Experience working with cross-functional teams (product management, marketing, engineering, customer success, etc). 
• An entrepreneurial mindset that emphasizes scrappiness, experimentation, and creativity - done is better than perfect
• Practical experience with content creation tools (e.g. Figma, Final Cut, Runway ML, Canva, etc.)