MLOps Engineer

Key Skills

Aartificial intelligence, Caffe, Data structuring, Flax Programming Language, HuggingFace, Keras software library, Machine learning techniques, MLOps tools, Natural Language Processing (NLP), NumPy, Pandas, Planning and organization, Python Programming, TensorFlow, TensorRT

Job Description

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 one of Clarifai's ML-OPS Engineers, you will have impact within the developer community, machine learning field, and on Clarifai's business by using state-of-the-art machine learning tools, assisting with our innovation engine, and transferring your deep learning knowledge to others at Clarifai.

The Opportunity

As a member of our Research Team, you will solve real world problems through a process of prototyping, implementation, measurement, and iteration. You'll research the latest developments in machine learning, understanding what works best for our users. You will develop models, techniques, and tools and integrate new machine learning capabilities into Clarifai's machine learning platform.

As an ML-OPS Engineer on our product team, you will research the latest tools and techniques in machine learning and determine their potential use in our platform. You will run experiments to test performance, consider optimizations, and improve the features that we offer. You will work on a team of scientists and engineers, and be responsible for staying up to date with the latest research, testing and experimenting with new ideas and techniques, and building what works best into our products.

We are looking for someone motivated to learn and experiment with new ideas, and who is interested in staying up to date with the latest research in machine learning. We are looking for candidates interested in project ownership - you will have the opportunity to determine the best way to figure out a solution to our problems, how to evaluate your solution, and how it could be best used by our team. An ideal candidate will love trying out new ideas and developing the ones that work best into usable software.

You will:

• Develop data processing workflows for optimized ingestion
• Develop SOTA data augmentation techniques
• Develop and Improve a robust experiment tracking system 
• Design KF pipelines for computationally intensive operations
• Build python-utils for internal and external uses

Requirements

• Fluent with using an NN framework such as TensorFlow, Keras, Caffe, or Torch, and understanding how back-propagation works
• Fluent with Python, as well as experience with packages such as NumPy, pandas, scikit-learn, and matplotlib.
• Experience with popular machine learning hubs and frameworks, such as hugging face, OpenMMLab, and detectron2
• PhD/Masters in Computer Science or related field 
• Kubernetes at a high level
• Familiar with ML hardware and related technology
• Knowledge on scaling ML

Great to Have

• Experience working in product teams
• Experience with GO programming language
• Experience with TensorRT, Deepstream, TRITON
• Projects in video, speech, or NLP
• Published Research papers/patents
• Contribution to open-source projects