This is a fully remote position, open to applicants in United States.

📋 Description

• Leverage data, embedding models, and personalization strategies to craft meaningful and tailored family history experiences.

• Design and assess models for customer segmentation, understanding user behavior, and tracking genealogy skill development.

• Enhance adaptive product experiences through effective customer and user modeling.

• Collaborate with applied scientists and software engineers to create, build, and implement scalable machine learning solutions.

• Aid in the areas of discovery, recommendations, customer insights, content exploration, personalization, and information retrieval.

• Engage in technical discussions and knowledge sharing initiatives.

• Convert research concepts into scalable, practical production systems.

⛳️ Requirements

• Currently enrolled in a master's or PhD program, expected to graduate in 2026.

• Pursuing an advanced degree (MS or PhD; PhD preferred) in Computer Science or a related discipline.

• Proven experience in applied research, including the implementation and adaptation of published machine learning models or methodologies to address real-world challenges.

• Previous publications in prestigious venues such as NeurIPS, ICML, ICLR, CVPR, ACL, KDD, or similar conferences are advantageous.

• Proficient in Python, SQL, and AWS.

• Practical experience with applied machine learning techniques and Hugging Face.

• Familiarity with embedding models, Retrieval-Augmented Generation (RAG), and representation learning is a plus.

• Skilled in deep neural networks and modern ML frameworks such as PyTorch or TensorFlow/Keras.

• Experience with large language models or generative AI applications, including prompt engineering, retrieval-augmented generation, or agent-based workflows.

• Background check required as a condition of employment.