Senior ML Ops Engineer

Job Title: Data/ML Ops Engineer Job Description: The backbone that keeps AI running. Manage data pipelines, model deployment, monitoring, and infrastructure automation to ensure reliable, scalable ML in production. Key Requirements: 4+ years in DevOps, Data Engineering, or MLOps Strong experience with Docker, Kubernetes, and CI/CD (GitHub Actions, GitLab CI) Hands-on with MLflow, Kubeflow, Airflow, or Prefect Experience with cloud platforms (AWS, Azure, Google Cloud Platform) and IaC (Terraform,

ML Ops Engineer RESPONSIBILITIES Architect and build a production-grade MLOps platform on Snowflake using Snowpark, Snowflake ML, Model Registry, and Feature Store capabilities. Design and operationalize reusable ML pipelines for training, validation, deployment, inference, and monitoring. Build MLOps workflows aligned with Bronze, Silver, and Gold layers so model training and inference consistently consume trusted medallion data. Establish model lifecycle management standards, including version

Required Qualifications Bachelor's degree in Information Systems or related field 3 6 years of experience in ML projects (with 18+ months in MLOps) Strong programming skills (Python, Java, or Scala) Experience with ML frameworks (TensorFlow, PyTorch, scikit-learn) Experience with Azure cloud platform Familiarity with Docker and Kubernetes Experience with ML deployment tools (MLflow, Kubeflow)

Job Family: Software Development & Support Travel Required: None Clearance Required: Ability to Obtain Public Trust What You Will Do Guidehouse Technology is seeking a highly skilled and motivated AI-focused Software Engineer to join our dynamic team. In this role, you will work with federal clients to design, develop, and deploy innovative Artificial Intelligence and Machine Learning solutions that address immediate mission challenges. You will be a key contributor on a team of data scienti