Staff AI Researcher - Generative AI

Summary

Join a rapidly growing healthcare technology company as a Staff AI Researcher in Generative AI to develop AI solutions improving health for millions. Partner with engineering and analytics teams, integrating AI into existing products and workflows. Lead the use of a vast medical data set for training and fine-tuning AI models. Build prototypes using various AI techniques, work with large datasets, and redesign pipelines to meet data needs. Develop evaluation metrics and implement feature engineering pipelines. Set engineering process standards and deliver working POC solutions.

Requirements

• BS/BTech (or higher) in Computer Science or a related field required
• 3+ years of relevant deep learning and LLM work experience
• 8+ years of relevant machine learning and statistical analysis experience
• 3+ years or Python language experience
• Experience in addressing challenges from incomplete, unrepresentative, and mislabeled data
• Experience working with large-scale distributed systems at scale and statistical software (e.g. Spark)
• 3+ years of demonstrated proficiency in selecting the right tools given a data optimization problem

Responsibilities

• Build working prototypes using off-the-shelf and novel AI techniques to deliver higher optimization levels for the company
• Work with large, complex data sets. Solve difficult, non-routine analysis problems to harvest data
• Re-design current pipelines and systems to meet the growing data and query needs
• Implement techniques for fine-tuning and adapting pre-trained generative models to specific healthcare domains or tasks
• Develop evaluation metrics and benchmarks to assess the quality and performance of AI/ML models
• Experience in designing and implementing feature engineering pipelines, including data processing, feature extraction, and transformation to optimize model performance
• Set and uphold the standard for engineering processes to support high-quality engineering, including style and code checking, test harnesses, and release packaging
• Deliver working POC solutions solving speed, scalability and time-to-market tradeoffs

Preferred Qualifications

• Ph.D. or Master's degree in a quantitative discipline (e.g., Computer Science[with AI/ML Major], Statistics, Operations Research, Economics, Mathematics, Physics) or equivalent practical experience
• Proficiency in communicating analysis and establishing confidence among audiences who do not share your disciplinary background or training
• Experience with security and systems that handle sensitive data
• Experience with Databricks/MLflow
• Experience with designing and implementing production-ready agentic systems
• Proficiency in at least one major deep learning framework (e.g. PyTorch, Tensorflow, Keras, etc), with the ability to design and implement deep learning architectures
• Demonstrated leadership and self-direction
• First-author publications at peer-reviewed conferences (e.g. NeurIPS, ICML, ACL, JSM, KDD, EMNLP)
• Winners in ACM-ICPC, NOI/IOI, Kaggle
• Working knowledge of health-tech systems, like Electronic Health Records, Clinical data, etc