What you'll do:

• Work on all aspects of a production machine learning system, including acquiring data, training and building models, deploying models, building API services for exposing these models, and maintaining them in production.
• Focus on performance tuning of models.
• Occasionally support and debug production systems.
• Research and apply the latest technology to build new products and enhance the existing platform.
• Build workflows for training and production systems.
• Contribute to documentation.

What makes you a great fit:

• Experience in framing and solving problems with machine learning or deep learning models.
• Expertise in either computer vision or natural language processing (NLP)is a must, with appropriate production system experience
• Experience with generative AI, including fine-tuning models and utilizing retrieval-augmented Generation (RAG)
• Understanding that modeling is only a small part of building and delivering AI solutions, and knowledge of what it takes to keep a high-performance system up and running.
• Proficiency in Python and experience with PyTorch, TensorFlow, JAX, HuggingFace, Spacy, etc.
• Enthusiasm and drive to learn and assimilate state-of-the-art research.
• Ability to write APIs.
• Experience with AI systems with at least one cloud provider: AWS Sagemaker, GCP VertexAI, AzureML
• Familiarity with languages like Go, and Elixir, or an interest in functional programming.
• Knowledge and experience in MLOps and tooling, particularly Docker and Kubernetes.
• Experience with other platforms, frameworks, and tools.