Staff AI Researcher- Generative AI

Primary Duties:

• 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.

Minimum Qualifications:

• 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. 

Preferred KSA’s:

• 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.

Physical Requirements:

• Sitting for prolonged periods of time. Extensive use of computers and keyboard. Occasional walking and lifting may be required.