Staff AI Researcher - Generative AI

Job not on LinkedIn

July 19

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Logo of Aledade, Inc.

Aledade, Inc.

Healthcare Insurance • Enterprise

Aledade, Inc. is a public benefit corporation that operates as the largest network of independent primary care practices in the United States. The company specializes in Accountable Care Organizations (ACOs), which help primary care practices and health centers improve patient outcomes and generate sustainable revenue through value-based care solutions. Aledade offers data insights, support, and business solutions to achieve sustainability and clinical autonomy. It collaborates with a wide range of healthcare providers, including primary care practices, community health centers, and network ACOs, ensuring improved quality of care and patient satisfaction. With operations in 45 states and affiliations with over 20,000 clinicians serving more than 2. 5 million patients, Aledade is committed to reducing care fragmentation and enhancing the overall quality of life for clinicians and patients alike.

đź“‹ Description

•As a Staff AI Researcher, you will develop AI solutions that will improve health for millions of people. •Here at Aledade we empower primary care physicians with technology to keep their patients healthy and prevent unnecessary hospitalizations. •You will partner with other engineering and analytics teams, bringing AI technology into existing products and workflows. •As a Staff AI Researcher, you will lead the way to harness knowledge from one of the most extensive data sets of medical records, diagnoses, claims, and prescriptions. •You will have a unique opportunity to train, fine-tune and use AI models using medical data we collect from millions of patients across the country.

🎯 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.

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