Machine Learning Engineer

Machine Learning Operations EngineerHow this Role Makes an Impact The Imagine team is a growing company, and we are inviting a motivated Machine Learning Operations Engineer to join our talented team! This candidate will play a critical role in bringing machine learning models into reliable, scalable production environments that support innovative healthcare solutions. The ideal candidate will combine strong technical expertise with a solutions-oriented mindset.If you are looking for a place that offers a challenging and fast-paced environment with the opportunity to grow and develop, look no further! We are always looking for quality people to join our growing team. Must-haves include the ability to adapt to an ever-changing environment, work quickly and efficiently, continuously challenge the status quo, and be an innovative and solutions-based thinker.Essential Duties MLOps Strategy & ArchitectureWork with senior leadership to define and lead the MLOps vision, architecture, and roadmap across model development and production environmentsDesign end-to-end ML pipelines, from data ingestion and feature engineering to training, validation, deployment, and monitoringEstablish scalable patterns for model lifecycle management (versioning, retraining, rollback, auditability)Model Development EnablementPartner with Data Science teams to productionize models efficiently and reliablyBuild and maintain tooling for experimentation, model tracking, and reproducibility (e.g., feature stores, experiment tracking systems)Optimize training workflows for performance, cost, and scalabilityProduction Infrastructure & DeploymentArchitect and manage cloud-native ML infrastructure in AWS (e.g., SageMaker, EKS, Lambda, S3, Step Functions)Implement CI/CD pipelines for ML workflows, including automated testing, validation, and deploymentEnable real-time and batch inference systems with high availability and low latencyMonitoring, Reliability & GovernanceEstablish monitoring for model performance, data drift, and system healthImplement alerting, logging, and observability frameworksEnsure compliance with security, privacy, and governance standardsOther duties as assignedEducation and/or Experience Needed BS in computer science, engineering, data science, or related technical field5+ years of experience in machine learning engineeringQualifications You Must Have 3+ years of hands-on experience in MLOps or production ML systemsDeep expertise in AWS cloud services (e.g., SageMaker, EKS, EC2, S3, IAM, CloudWatch)Strong programming skills in Python (and ideally one additional language such as Java)Experience building and maintaining ML pipelines and orchestration tools (e.g., Airflow, Kubeflow, Step Functions)Strong understanding of CI/CD practices and DevOps principlesExperience with feature stores, model registries, and experiment tracking tools (e.g., MLflow, Feast)Familiarity with streaming/data processing frameworks (e.g., Kafka, Spark)Experience supporting both real-time and batch ML systemsKnowledge of model governance, fairness, and explainability frameworksEmployment Type Full Time, ExemptReporting Structure Sr. Vice President, Data ScienceLocation & Work AuthorizationCharlotte, NC is the preferred location for this position.This position is not eligible for H-1B visa sponsorship or C2C (Corp-to-Corp) arrangements. Candidates must be authorized to work in the United States without employer sponsorship, now or in the future.At ImagineSoftware, we have a role to play in contributing to an inclusive world. We work every day to lead with our values and beliefs that enable you to develop your potential and bring your full self to the workplace. Our culture of diversity and inclusion enables more creative thinking and better ideas for addressing a more diverse market. We hire driven people from all backgrounds because it makes us a great company, and because it’s the right thing to do. If you share these values, you will find a home at ImagineSoftware.