Senior ML/AI Researcher II

Employment Type: Full Time

Position Overview

Aledade is seeking a Senior ML/AI Researcher II to develop machine learning and AI solutions aimed at improving health outcomes for millions of individuals. We empower primary care physicians with technology to enhance patient health and prevent unnecessary hospitalizations. In this role, you will collaborate with engineering and analytics teams to integrate AI technology into our existing products and workflows. You will have the opportunity to work with one of the most extensive data sets of medical records, diagnoses, claims, and prescriptions, enabling you to train, fine-tune, and utilize AI models on medical data from millions of patients nationwide.

Primary Duties

• Train and fine-tune models using off-the-shelf and novel ML/AI techniques to solve optimization problems for the company.
• Work with large, complex data sets, conducting difficult, non-routine analysis and harvesting data.
• Deliver working Proof of Concept (POC) solutions, balancing speed, scalability, and time-to-market considerations.

Minimum Qualifications

• BA/BTech in Statistics, Data Science, Computer Science, or a related field.
• 6+ years of relevant statistical analysis experience.
• 6+ years of relevant machine learning experience (ML modeling, hyperparameter tuning, feature engineering, model validation, etc.).
• Understanding of causal inference and treatment effects estimation.
• 3-5 years of experience selecting, implementing, and optimizing ML tools and frameworks for large-scale projects.
• 2+ years of Python language experience.
• 1+ years of relevant deep learning and LLM experience.
• 1+ years of experience working with large-scale distributed systems and statistical software (e.g., Spark).
• Experience in addressing challenges arising from incomplete, unrepresentative, and mislabeled data.
• Contributions to the field (e.g., publications, patents, or successful large-scale implementations).

Preferred Qualifications (KSA's)

• Master's or PhD degree in a quantitative discipline (e.g., Computer Science with AI/ML Major, Statistics, Operations Research, Economics, Mathematics, Physics) or equivalent practical experience.
• Background in Epidemiology, particularly in the context of chronic condition modeling.
• Working knowledge of Public Health, with a focus on Value-Based Care and Risk Adjustment.
• Working knowledge of health-tech systems, such as Electronic Health Records and clinical data.
• Proficiency in communicating analysis and establishing confidence among audiences with diverse disciplinary backgrounds.
• Experience with security and systems that handle sensitive data.
• Experience working with statistical software (e.g., R, SAS, Python statistical packages).
• Demonstrated leadership and self-direction.
• Publications at peer-reviewed conferences (e.g., NeurIPS, ICML, ACL, JSM, KDD, EMNLP).
• Participation in ACIC Data Challenges, Kaggle, etc.

Physical Requirements

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