AI Engineer at Ensemble Health Partners in Remote

AI Engineer Location: Remote - Nationwide Thank you for considering a career at Ensemble! Ensemble is a leading provider of technology-enabled revenue cycle management solutions for health systems, including hospitals and affiliated physician groups. They offer end-to-end revenue cycle solutions as well as a comprehensive suite of point solutions to clients across the country. Ensemble keeps communities healthy by keeping hospitals healthy. We recognize that healthcare requires a human touch, and we believe that every touch should be meaningful. This is why our people are the most important part of who we are. By empowering them to challenge the status quo, we know they will be the difference! O.N.E Purpose: Customer Obsession: Consistently provide exceptional experiences for our clients, patients, and colleagues by understanding their needs and exceeding their expectations. Embracing New Ideas: Continuously innovate by embracing emerging technology and fostering a culture of creativity and experimentation. Striving for Excellence: Execute at a high level by demonstrating our “Best in KLAS” Ensemble Difference Principles and consistently delivering outstanding results. The Opportunity: By embodying our core purpose of customer obsession, new ideas, and driving innovation, and delivering excellence, you will help ensure that every touchpoint is meaningful and contributes to our mission of redefining the possible in healthcare. The Lead Engineer, AI is responsible for building AI and Machine learning models and pipelines, with a focus on generative AI, LLMs and predictive modelling. The successful candidate will work closely with data scientists and product leads to implement AI models, build required data and code pipelines through rigorous engineering disciplines You should have expertise in the design, development, management, and maintenance of systems and handling of large datasets. You should have hands on experience with common machine learning and AI frameworks, and a good knowledge of AI and machine learning fundamentals (deep learning, regression, classification and clustering algorithms), retrieval augmented generation pipelines, as well as a good grasp of the design and evaluation of LLM-supported use cases. Essential Job Functions Customer Obsession: Consistently provide exceptional experiences for our clients, patients, and colleagues by understanding their needs and exceeding their expectations. Embracing New Ideas: Continuously innovate by embracing emerging technology and fostering a culture of creativity and experimentation. Striving for Excellence: Execute at a high level by demonstrating our “Best in KLAS” Ensemble Difference Principles and consistently delivering outstanding results. Coordinate between Data Scientists and Product Analysts Automate infrastructure used by the Data Science team Test and deploy models Develop minimum viable products based on machine learning Automate processes by utilizing machine learning Ability to create AI models utilizing deep learning, neural networks, and ML algorithms to derive business insights and fuel informed decision-making Well versed in programming, software engineering, and data science fields Ability to utilize various tools and methods to process data as well as create and keep up AI systems Lead and manage AI projects, ensuring timely delivery and high-quality outcomes. Design, develop, and deploy advanced AI models and algorithms to solve complex business problems. Communicate findings and recommendations to stakeholders through clear and compelling data visualizations and presentations. Advanced skills in programming, software engineering, and data science fields Mentor and coach junior associates on the team Employment Qualifications Desired Work Experience 7 to 10 Years Desired Education Post Graduate Degree or Equivalent Experience Computer Science Other Preferred Knowledge, Skills and Abilities Bachelors or Masters in Computer Science / Machine Learning / AI, or related work experience with the design, building and evaluation of Machine Learning systems. 5+ 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. 5+ years of experience working with and evaluating LLM-based pipeline, with an emphasis on retrieval augmented generation and prompting techniques Expert level of 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. Expert knowledge of langchain / llamaindex / haystack / Azure AI studio, vector databases and Expertise handling databases via SQL, Azure Data Factory or similar. Alternatively, familiarity with data storage/management systems or Big Data frameworks (like Hadoop, Spark) expected to be known or used. Expert knowledge in Software Development best practices such as Continuous Integration, Unit/Integration Testing, Code Reviews. Excellent communication skills, both written and verbal. Knowledge of Revenue Cycle Management, Collections, or financial industries is desirable but not necessary. Must be inquisitive and demonstrate openness to innovation including AI to explore better processes and ways to alleviate friction and improve patient and client experiences. This is a remote position; however, candidates must be willing and able to travel to and work onsite at client, temporary, or corporate office locations as business needs require. #LI-BT1 #LI-REMOTE Join an award-winning company Five-time winner of “Best in KLAS” 2020-2022, 2024-2025 Black Book Research's Top Revenue Cycle Management Outsourcing Solution 2021-2024 22 Healthcare Financial Management Association (HFMA) MAP Awards for High Performance in Revenue Cycle 2019-2024 Leader in Everest Group's RCM Operations PEAK Matrix Assessment 2024 Clarivate Healthcare Business Insights (HBI) Revenue Cycle Awards for strong performance 2020, 2022-2023 Energage Top Workplaces USA 2022-2024 Fortune Media Best Workplaces in Healthcare 2024 Monster Top Workplace for Remote Work 2024 Great Place to Work certified 2023-2024 Innovation Work-Life Flexibility Leadership Purpose + Values Bottom line, we believe in empowering people and giving them the tools and resources needed to thrive. A few of those include: Associate Benefits –  We offer a comprehensive benefits package designed to support the physical, emotional, and financial health of you and your family, including healthcare, time off, retirement, and well-being programs. Our Culture – Ensemble is a place where associates can do their best work and be their best selves. We put people first, last and always. Our culture is rooted in collaboration, growth, and innovation. Growth – We invest in your professional development. Each associate will earn a professional certification relevant to their field and can obtain tuition reimbursement. Recognition – We offer quarterly and annual incentive programs for all employees who go beyond and keep raising the bar for themselves and the company. Ensemble is an equal employment opportunity employer. It is our policy not to discriminate against any applicant or employee based on race, color, sex, sexual orientation, gender, gender identity, religion, national origin, age, disability, military or veteran status, genetic information or any other basis protected by applicable federal, state, or local laws.  Ensemble also prohibits harassment of applicants or employees based on any of these protected categories. Ensemble provides reasonable accommodations to qualified individuals with disabilities in accordance with the Americans with Disabilities Act and applicable state and local law. If you require accommodation in the application process, please contact TA@ensemblehp.com. This posting addresses state specific requirements to provide pay transparency.  Compensation decisions consider many job-related factors, including but not limited to geographic location; knowledge; skills; relevant experience; education; licensure; internal equity; time in position.  A candidate entry rate of pay does not typically fall at the minimum or maximum of the role’s range. Employment Disclaimers – Ensemble