Lead AI Research Engineer

Ensemble Health Partners is a leading provider of technology-enabled revenue cycle management solutions for health systems. The Senior Engineer, AI is responsible for building AI and Machine learning models and pipelines, focusing on generative AI and predictive modeling, while collaborating with data scientists and product leads. Responsibilities: Coordinate between Data Scientists and Product Analysts; Automate infrastructure used by the Data Science team; Design, develop, and deploy advanced AI models and algorithms to solve complex business problems; Test and deploy models; Develop minimum viable products based on machine learning; Automate processes by utilizing machine learning; Lead AI projects from conception to implementation, ensuring timely delivery and high-quality outcomes; Ability to create AI models utilizing deep learning, neural networks, and ML algorithms to derive business insights and fuel informed decision-making; Advanced experience in programming, software engineering, and data science fields; Mentor and coach junior associates on the team; Ability to utilize various tools and methods to process data as well as create and keep up AI systems; Communicate findings and recommendations to stakeholders through clear and compelling data visualizations and presentations Qualifications: 5 to 7 Years of desired work experience; Bachelors Degree or Equivalent Experience; 5+ years of practical experience as an engineer with focus on implementation of AI / ML machine learning solutions; Masters in Computer Science / Machine Learning / AI, or related work experience with the design, building and evaluation of Machine Learning systems; 3+ years' experience with Machine Learning ecosystem tools, including pytorch/tensorflow, scikit-learn, xgboost or equivalents; Advanced knowledge of MLOps fundamentals, including orchestration tools, cloud compute, and observability tools; Advanced understanding of cloud platforms e.g. Azure / GCP / AWS and their AI tool set; Practical experience working with data and code pipelines; Ability to work independently with limited supervision; Ability to implement, test and deploy Machine Learning models; Advanced experience with langchain / llamaindex / haystack / Azure AI studio, vector databases and retrieval techniques, or equivalent common tools in the emerging LLM-enable tech stack is a plus; Skilled in accessing and handling databases via SQL, Azure Data Factory or similar; Alternatively, familiarity with data storage/management systems or Big Data framework (like Hadoop, Spark) expected to be known or used; Advanced knowledge in Software Development best practices such as Continuous Integration, Unit/Integration Testing, Code Reviews; Excellent communication skills, both written and verbal Required Skills: Artificial Intelligence, Machine Learning, Generative AI, Large Language Models, Predictive Modeling, Deep Learning, Regression, Classification, Clustering Algorithms, Retrieval Augmented Generation, AI Model Design, AI Model Evaluation, Data Pipeline Development, Code Pipeline Development, PyTorch, TensorFlow, Scikit-learn, XGBoost, MLOps, Cloud Platforms, Azure, Google Cloud Platform, Amazon Web Services, Langchain, LlamaIndex, Haystack, Azure AI Studio, Vector Databases, SQL, Azure Data Factory