Job Description
Responsibilities and Qualifications
- 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
- Advanced proficiency in Python programming with a focus on writing clean, testable and efficient code
- DevOps & Containers: Proficient with Docker for containerization and working knowledge of Kubernetes (k8s) for orchestration