Senior Software Engineer, AI/ML, Search Discover Personalization

Job description

Innovate on the methodology of understanding user's interests. Develop and apply state of the art techniques for content retrieval. Collaborate with partners and teammates to understand the user problems and opportunities for applying personalization. Work with the large-scale user data to generate desired training data in a reliable and scalable manner. Implement and experiment with different state of art ML algorithms and model architectures, including but not limited to LLM, deep learning, distillation, etc. Iterate on the model quality via evals, demos and LEs to realize positive product impacts. Leverage the user understanding model to retrieve content across content formats (articles, posts, videos, AI generated content, etc.). Integrate models/components with Discover stack to ensure system efficiency and effectiveness. Take full ownership of projects, including ideation, implementation, analysis, and maintenance. Minimum Qualifications: Bachelor’s degree or equivalent practical experience. 5 years of experience with software development in Python. 3 years of experience testing, maintaining, or launching software products and 1 year of experience with software design and architecture. 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). 3 years of experience developing and optimizing deep learning algorithms and architectures. 3 years of experience with one or more of the following: reinforcement learning (e.g., sequential decision making), recommendations/ranking, LLMs, ML infrastructure, or specialization in another ML field. Preferred Qualifications: Master's degree or PhD in Computer Science or related technical field. 3 years of experience with machine learning algorithms and tools (e.g. JAX, TensorFlow, deep learning, natural language processing, LLM based applications, LLM finetuning, etc.). Experience with user understanding and personalization and a passion for diving deep into recommender systems. High level of mathematical aptitude, demonstrated problem-solving skills, and proven logical, analytical, and investigative thinking.