Requirements

Candidates should possess at least 4 years of experience building and deploying large-scale AI/ML solutions within an agile engineering team, with a focus on personalization, predictive modeling, and automated decision-making. Strong experience in data engineering, including building and maintaining data pipelines, integrating data for model training, and deploying models on cloud platforms such as AWS, Azure, or Databricks is required. Proficiency with ML frameworks like TensorFlow, PyTorch, and Hugging Face, along with familiarity with OpenAI and open-source LLMs like GPT and BERT, is essential. Expertise in machine learning techniques including unsupervised learning, reinforcement learning, and deep learning, combined with the ability to optimize AI models for scalability and efficiency in production environments, is also needed.