Role Summary:
Develop, deploy and operationalize machine-learning and applied-AI solutions from model development through productionization that improve clinical and operational decision-making across Aledade's platform.
Key responsibilities
Build, train, evaluate and deploy ML models and LLM/GenAI-based solutions into production.
Develop ML pipelines, feature stores and serving infrastructure; monitor model performance and drift.
Collaborate with product and engineering to integrate AI capabilities into customer-facing workflows.
Translate ambiguous business problems into well-scoped, measurable AI solutions.
Skills:
Python SQL AWS
Hands-on ML engineering in Python (PyTorch/TensorFlow/scikit-learn); SQL for feature and data work; deploying ML workloads on AWS (SageMaker, Bedrock, Lambda, S3).
LLM / GenAI, RAG, prompt engineering, vector databases.
MLOps tooling (MLflow, Kubeflow, model registries).
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.
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