Job Description:

• Design and develop models to extract entities, detect intents, and understand document structure
• Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs
• Evaluate model performance where ground truth is partial, uncertain, or evolving
• Shape the roadmap and success metrics for replacing legacy document processing systems with smarter, scalable solutions
• Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines
• Understand product use-cases and define key performance metrics for models according to business requirements
• Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.)

Requirements:

• 3+ years of experience with data science and machine learning in an industry setting
• Proficiency with Python
• Experience with the latest in language models (transformers, LLMs, etc.)
• Proficiency with standard data analysis toolkits such as SQL, Numpy, Pandas, etc.
• Proficiency with deep learning frameworks like PyTorch (preferred) or TensorFlow
• Industry experience shepherding ML/AI projects from ideation to delivery
• Demonstrated ability to influence company KPIs with AI
• Demonstrated ability to navigate ambiguity

Benefits:

• Building systems that make healthcare data more usable, accurate, and safe
• Health insurance
• Professional development opportunities