Develop, program, and test machine learning systems
Design architectures for reproducible, scalable, and monitored Machine Learning solutions
Assist the data science team in designing and building model deployment pipelines
Build data engineering processes/pipelines within the data environment
Define architecture standards, procedures, and tooling
Define data layers and their intended usage
Implement, fine-tune, and monitor LLM models (e.g., Bedrock, OpenSearch, HuggingFace)
Build inference pipelines for RAG-based responses (Retrieval-Augmented Generation)
Ensure versioning and reuse of trained models and embeddings
Work on continuous improvement of response relevance and source ranking
Work on reducing token costs using optimization techniques
Support integrations with AI APIs, vector stores, and document repositories
Communicate information clearly with technical and business team members
Help identify potential errors and report inconsistencies

Machine Learning Engineer – AWS, Mid/Senior

Key skills