Key skills
MLOpsPythonDockerKubernetesMLflowCI/CD pipelinestime series datasetsmonitoring toolsFluent EnglishMachine LearningMLGenAILangChainLangGraphAnalyticsVersion ControlCI/CDCollaboration
About this role
Madiff is seeking an MLOps Engineer to support a sports analytics and performance intelligence platform used by professional basketball organizations, including NBA teams. The role involves deploying machine learning models, building and maintaining pipelines, and collaborating with data scientists to enhance model lifecycle management.
Responsibilities:
- Deploy and operate machine learning models supporting sports analytics use cases
- Build and maintain pipelines for model training, validation, and deployment
- Support high frequency and time series data processing workflows
- Deploy and manage LangChain and LangGraph based GenAI services
- Implement monitoring for model performance, drift, and data quality
- Ensure reproducibility and version control for models and datasets
- Support fast iteration and experimentation in production-like environments
- Collaborate closely with data scientists and engineers to streamline model lifecycle
Requirements:
- Strong experience in MLOps or ML platform engineering
- Solid Python skills for automation and tooling
- Hands on experience with Docker and Kubernetes
- Experience with MLflow or similar model lifecycle management tools
- Experience building CI/CD pipelines for ML workloads
- Experience working with high volume or time series datasets
- Basic experience with monitoring and observability tooling
- Fluent English for collaboration in an international team
- Experience deploying LangChain or LangGraph based services
- Background in sports analytics or performance data
- Experience working in fast paced product environments
- Familiarity with real time or streaming data architectures