What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- AI/ML Engineering and production deployment experience
- Generative AI and RAG architecture knowledge
- MLOps including deployment monitoring and CI/CD
- AWS experience with SageMaker Lambda S3 ECS or EKS
- Proficiency in Python PyTorch TensorFlow LangChain Docker and Kubernetes
- Ability to collaborate with engineering data and product teams
Day to day
- Design and deploy ML and Generative AI solutions from development to production
- Build scalable pipelines and cloud-native AI applications for AI/ML workloads
- Implement Retrieval-Augmented Generation solutions and orchestration workflows to enhance contextual AI systems