Design, develop and deploy machine learning solutions and services
Implement end-to-end machine learning pipelines from data ingestion to training and model serving
Operationalize LLMs, embeddings, and multi-agent systems in real-world applications
Manage the machine learning and model lifecycle (experimentation, registry, deployment)
Oversee the model promotion lifecycle, coordinating validation gates and approval workflows to safely deploy new model versions from stating to production
Containerize applications using Docker and orchestrate them via Kubernetes
Build and maintain CI/CD pipelines for ML models and LLM applications
Collaborate with data scientists to refactor research code into production-ready Python code
Monitor model performance, data drift, and performance in production
Assess and integrate AI solutions ensuring optimal performance and relia...