MLOps Engineer – Sports Analytics and Performance Intelligence (NBA)
This is a remote position.
We are looking for an MLOps Engineer to support a sports analytics and performance intelligence platform used by professional basketball organisations, including NBA teams. The platform processes large volumes of historical and near real time player, workload, and game event data.Machine learning models generate insights consumed by analysts, coaches, and front office teams, while LangChain and LangGraph based GenAI components orchestrate comparisons, narratives, and interactive exploration. The environment prioritises speed, scalability, and practical impact in live analytical workflows.
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
Nice to have
• 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
Apply Now
Apply Now
We are looking for an MLOps Engineer to support a sports analytics and performance intelligence platform used by professional basketball organisations, including NBA teams. The platform processes large volumes of historical and near real time player, workload, and game event data.Machine learning models generate insights consumed by analysts, coaches, and front office teams, while LangChain and LangGraph based GenAI components orchestrate comparisons, narratives, and interactive exploration. The environment prioritises speed, scalability, and practical impact in live analytical workflows.
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
Nice to have
• 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
Apply Now
Apply Now