An industry-leading technology and analytics organization is hiring an AI/ML Operations Engineer to support its rapidly growing artificial intelligence initiatives. This full-time opportunity offers the chance to work with modern cloud technologies, machine learning platforms, containerized environments, and production AI systems. The ideal candidate will have experience deploying machine learning solutions, building cloud infrastructure, and supporting MLOps best practices across enterprise env

Role: ML Ops Engineer Duration: Full time Location: Remote Overview Seeking an experienced ML Ops Engineer to build and operate scalable ML infrastructure supporting predictive models, NLP, and LLM applications in a healthcare environment. The role focuses on automation, deployment, monitoring, governance, and HIPAA-compliant ML operations. Key Responsibilities Build automated ML training, evaluation, and deployment pipelines using MLflow, Databricks Workflows, and AWS SageMaker.Manage model ser

looking for a Senior Software / ML Engineer with strong MLOps experience who can help bridge the gap between traditional data science work and production engineering. This team has historically operated more like a traditional Data Science organization, with models being developed and trained primarily in Databricks. The team is now evolving toward a stronger engineering model where those machine learning outputs need to be operationalized and made available to real production systems. The ide

CTG is seeking to fill a Machine Learning Engineer position for our client. Location: Remote Duration: 12 months Duties: Build and maintain production-grade data pipelines (batch and streaming) with clear SLAs, retries, idempotency, and automated backfills.Integrate and model data across sources by defining schemas, keys, transformations, and curated layers that support analytics and ML consumption.Implement data quality, observability, and governance controls, including validation rules, lin