Machine Learning Engineer

What you'll do

• Design, optimize, and deploy personalized, context-aware experiences using semantic retrieval and ranking models.
• Build semantic retrieval, embedding, reranking, and retrieval-augmented generation systems to improve search quality.
• Improve underlying software infrastructure and optimize solutions for low-latency inference.
• Adapt large foundation models into smaller, efficient models for on-device memory and compute constraints.
• Implement model optimization techniques such as quantization, pruning, or knowledge distillation.
• Design and run offline evaluations and online A/B testing to measure model performance and search quality.
• Transition AI capabilities from research into production environments to drive technical strategy.

What we're looking for

• Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field (preferred).
• Background in machine learning, deep learning, natural language processing, information retrieval, search, recommender systems, or generative AI.
• Experience with semantic retrieval, embedding models, reranking, or retrieval-augmented generation systems.
• Programming skills in Python and/or C/C++ using frameworks such as PyTorch, JAX, or TensorFlow.
• Experience building and deploying semantic search, retrieval, or ranking systems at scale in a production environment (preferred).
• Experience adapting or distilling large foundation models into compact, efficient models for on-device deployment (preferred).
• Familiarity with model optimization techniques such as quantization, pruning, or knowledge distillation (preferred).