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
Basic qualifications
- 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
Preferred qualifications
- 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
Benefits
- Solid, competitive salary
- Work in a multinational environment on international projects
- Comprehensive healthcare
- Long-term B2B contract with a stable project pipeline
- Remote work model
Tags & focus areas
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