Job
Description
Acentra delivers a broad range of healthinformation technology enterprise solutions and customizable products to adiverse base of state and federal agencies. We align, build, and manageinnovative, high-quality, cost-effective solutions that help customers achievetheir mission, enhance business performance, reduce costs, and improve thehealth of over 50 million Americans. With locations throughout the U.S. and inIndia, Acentra employs a world-class team of technologists, healthcaresubject-matter experts, and program managers, all of whom have experience withlarge-scale mission-critical information technology implementations. Innovation and commitment to our missionare core to our DNA. And through our shared values, we foster an environment ofinclusion, empowerment, accountability, and fun! About the Job This position is for a Machine Learningexpert who is responsible for successful delivery of Acentra Health'stechnology initiatives. Candidates for this role will be working at theintersection of data science and software engineering, building, deploying, andoptimizing machine learning (ML) models and pipelines, with a strong emphasison large language models (LLMs), generative AI (GenAI), and natural languageprocessing (NLP). Will help improve patient outcomes and drive innovation andefficiency in healthcare. What you will do Design, develop, and implement ML models and algorithms to solvehealthcare-related problems, such as disease prediction, patient riskstratification, clinical decision support, and personalized medicine Exploreand implement state-of-the-art ML techniques, including supervised andunsupervised learning, deep learning, and NLP Develop and implement data cleaning, feature engineering, and dataaugmentation techniques to improve model performance and generalizability Evaluate and validate ML models using appropriate metrics andmethodologies, ensuring robustness, accuracy, and reliability Interpretand communicate model results to domain experts and stakeholders, providingactionable insights and recommendations Optimize models for performance, scalability, and real-timepredictions, considering computational constraints and regulatory requirements Design and develop innovative solutions using LLMs and foundationmodels to solve business problems and create operational efficiencies Lead the AI and ML development process and oversee CICD pipelines Document code, methodologies, and experimental results to ensurereproducibility and knowledge sharing Train junior level engineers and serve as a mentor for learningnew technologies, best practices, and company culture Collaborate with cross-functional teams, including datascientists, clinicians, researchers, and product managers, to translatebusiness requirements into technical solutions Stayabreast of the latest advancements in ML, AI, LLMs, healthcare informatics, andregulatory landscape to inform decision-making and drive innovation Who you are: Education : Bachelors degree in computer science, data science, or a relatedfield. 2+ Provenexperience and success as an ML Engineer. Technicalskills 2+ years of experience as a ML Engineer 2+ years of experience with object-oriented scripting languages, such as Python or R 2+ years of experience with developing ML models and NLP techniques 2+ years of experience with data preprocessing and feature engineering 2+ years of experience with LLMs and GenAI 1+ years of cloud computing experience using Azure and/or Amazon Web Services (AWS) for testing, deploying, and managing ML and AI systems Proven experience with successfully deploying solutions using LLMs and foundation models Proven experience with GenAI techniques such as variational autoencoders (VAEs), generative adversarial networks (GANs) and transformer-based models Provenexperience successfully developing and deploying ML algorithms, statisticalanalysis, and data mining techniques Proven experience mentoring ML Engineers and colleagues Demonstrable experience developing innovative ideas and solutions Goodto have familiarity with healthcare data standards (e.g., HL7, FHIR),electronic health records (EHR), medical imaging formats (DICOM), and relevanthealthcare regulations (e.g., HIPAA) is highly desirable
