About the Company

Clarifai is a leading, compute orchestration AI platform specializing in computer vision & generative AI. We empower organizations to transform unstructured image, video, text, & audio data into actionable insights, significantly faster & more accurately than manual processes. Founded in 2013 by Matt Zeiler, 

Ph.D., Clarifai has been at the forefront of AI innovation since achieving the top five placements in the 2013 ImageNet Challenge. Our diverse, globally distributed team operates across the United States, Canada, Estonia, Argentina, & India.

We have secured $100M in funding, including a $60M Series C round, backed by industry leaders such as Menlo Ventures, Union Square Ventures, Lux Capital, NEA, LDV Capital, Corazon Capital, Google Ventures, NVIDIA, Qualcomm, & Osage.

Clarifai is proud to be an equal-opportunity workplace committed to building & maintaining a diverse & inclusive team.

Key Responsibilities

• Identify trending open-source AI models with strong community adoption, import them into the Clarifai Community, & validate them across real-world use cases.
• Create clear, engaging previews & demosboth technical & non-technicalthat showcase model capabilities.
• Collaborate with Marketing to promote new models & generate compelling content around them.
• Engage with the open-source AI community to build relationships with original model authors & increase backlink visibility.
• Develop lightweight Python-based demos & utilities to highlight model performance & usability.

Impact

As an ML Community Ops Engineer, you will directly contribute to growing Clarifais model ecosystem by adding cutting-edge AI models & making them accessible to users. Your work will expand Clarifais reach, improve discoverability, & ensure our platform remains at the forefront of open-source AI. By bridging engineering, marketing, & community engagement, youll help solidify Clarifais presence in the AI developer ecosystem.

Requirements

• Strong experience developing, fine-tuning, & evaluating machine learning models, including familiarity with model architectures & key evaluation metrics.
• Expertise in deep learning frameworks (e.g., PyTorch, TensorFlow, JAX) & architectures such as transformers & CNNs.
• Actively follows AI & ML trendsstaying current with emerging models, benchmarks, & communities.
• Proficiency in Python, with ability to write clean, efficient code for ML workflows & data pipelines.
• Experience working with cloud platforms (e.g., AWS, GCP, Azure) for model deployment & compute orchestration.
• Solid software engineering fundamentals, including Git, modular design, & code testing.
• Practical experience with data preprocessing, feature engineering, & analysis of large datasets.

Great to Have

• Strong experience developing, fine-tuning, & evaluating machine learning models, including familiarity with model architectures & key evaluation metrics.
• Expertise in deep learning frameworks (e.g., PyTorch, TensorFlow, JAX) & architectures such as transformers & CNNs.
• Actively follows AI & ML trendsstaying current with emerging models, benchmarks, & communities.
• Proficiency in Python, with ability to write clean, efficient code for ML workflows & data pipelines.
• Solid software engineering fundamentals, including Git, modular design, & code testing.
• Practical experience with data preprocessing, feature engineering, & analysis of large datasets.