As a Staff AI Researcher, you will create AI solutions that enhance the health of millions of people. At Aledade, we equip primary care physicians with technology that helps them keep patients healthy and avoid unnecessary hospital visits. You will collaborate with engineering and analytics teams to integrate AI capabilities into existing products and workflows.

In this role, you will take the lead in leveraging one of the nation’s largest datasets of medical records, diagnoses, claims, and prescriptions. You will have a rare opportunity to train, fine‑tune, and apply AI models using medical data collected from millions of patients across the country.

Primary Duties:
• Build functional prototypes using both existing and new AI methods to improve company-wide optimization.
• Work with large, complex datasets and solve challenging, unconventional analytical problems to extract insights.
• Redesign current pipelines and systems to support increasing data volumes and query demands.
• Apply techniques for fine‑tuning and customizing pre‑trained generative models for specific healthcare tasks or domains.
• Create evaluation metrics and benchmarks to measure AI/ML model quality and performance.
• Design and implement feature engineering workflows, including data processing, feature extraction, and transformations that improve model performance.
• Establish and maintain engineering standards, including code quality checks, testing frameworks, and release processes.
• Deliver functional proof‑of‑concept solutions that balance speed, scalability, and time‑to‑market.

Minimum Qualifications:
• BS/BTech or higher in Computer Science or a related field.
• Over 3 years of experience in deep learning and large language models.
• Over 8 years of experience in machine learning and statistical analysis.
• At least 3 years of experience with Python.
• Experience handling incomplete, biased, or mislabeled data.
• Experience with large‑scale distributed systems and statistical tools such as Spark.
• At least 3 years of demonstrated ability to choose appropriate tools for data optimization problems.

Preferred Knowledge, Skills, and Abilities:
• PhD or Master’s degree in a quantitative field (such as Computer Science with an AI/ML focus, Statistics, Operations Research, Economics, Mathematics, or Physics), or equivalent applied experience.
• Strong communication skills, especially when explaining analyses to non‑experts.
• Experience with security and systems that manage sensitive data.
• Proficiency in at least one major deep learning framework (such as PyTorch, TensorFlow, or Keras) and ability to design deep learning models.
• Experience using statistical software such as R, SAS, or Python‑based statistical tools.
• Demonstrated leadership and ability to work independently.
• First‑author publications in peer‑reviewed conferences such as NeurIPS, ICML, ACL, JSM, KDD, or EMNLP.
• Recognition in competitions such as ACM‑ICPC, NOI/IOI, or Kaggle.
• Familiarity with health‑tech systems such as electronic health records and clinical data systems.

Physical Requirements:
• Ability to sit for long periods, work extensively on a computer and keyboard, and occasionally walk or lift items.