Senior Machine Learning Software Engineer

Responsibilities We are seeking a senior machine learning software engineer to design, build, deploy, monitor, and optimize production-ready ML services in regulated healthcare. You will work hands-on to package, test, orchestrate, deploy, and maintain ML models, improve workflows, and implement CI/CD and automated testing to ensure reliability, performance, and faster delivery of business value Collaborate with AI scientists to package and deploy ML models, ensuring reproducibility, versioning, and compliance Build and maintain model serving infrastructure including monitoring, drift detection, automated retraining, and logging Implement unit, integration, and system-level testing for ML models, covering data validation, model correctness, and deployment workflows Develop and operate end-to-end ML pipelines: ingestion -> preprocessing -> feature engineering -> evaluation -> deployment -> monitoring Integrate CI/CD and MLOps practices for automated model builds, testing, and deployment Identify and resolve workflow inefficiencies or gaps between research and production Recommend and integrate frameworks, libraries, and infrastructure to improve pipeline efficiency, maintainability, and observability Collaborate cross-functionally to ensure compliance with regulatory requirements (FDA/HIPAA) in production ML workflows Benefits Comprehensive benefits package to support your health, growth, and work-life balance Choose from a variety of medical, dental, and vision plans that suit your needs We also offer an Employee Assistance Program (EAP) Flexible self-managed PTO Company holidays, including the week between Christmas Eve & New Year's Day, so you can recharge 401K with company match Generous parental leave Monthly stipends for WiFi/Internet and wellness Support your professional growth with annual stipends for learning and development Home office support Requirements Experience with CI/CD, Orchestration tools (Airflow, MLflow, Kubernetes, Terraform) and ML/data platforms (SageMaker, Databricks, Unity Catalog, Snowflake/Snowpark) to build scalable ML data pipelines and model workflows Experience with unit, integration, and pipeline-level testing for ML models, including data validation, correctness checks, and reproducibility Familiarity with cloud platforms (AWS preferred: SageMaker, S3, EC2) and reproducible ML pipelines Proficiency in Python (required), Java, or similar, with software engineering best practices for ML workflows Hands-on experience deploying ML models via APIs, batch pipelines, or streaming inference 7+ years of experience in software engineering for ML production or ML platform delivery Strong collaboration skills to work effectively with AI scientists, software engineers, and regulatory teams #J-18808-Ljbffr Cleerly, LLC