Data AI Architect
MGMA
AzureCloudPythonSQLTableau
Job Level
Junior
Tech Stack
CloudIoTPythonPyTorchTensorflow
About the role
- Support the development, testing, and deployment of ML/GenAI models for product features like proposal scoring, document summarization, and intelligent routing.
- Partner with Data Engineering teams to scope and execute ingestion, transformation, and labeling tasks that prepare datasets for AI workloads.
- Analyze customer usage data and platform signals to uncover new AI opportunities and provide input on feature feasibility and design.
- Conduct data analysis on AI feature adoption, usage patterns, and outcomes to inform value-based packaging and monetization strategies.
- Build POCs, run evaluation frameworks, and benchmark model performance across tasks in support of iterative, agile development cycles.
- Assist with implementation, testing, and QA across dev environments to support production readiness and ongoing model monitoring.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field, or equivalent hands-on experience.
- 1–3 years of experience working on AI/ML projects, with exposure to model development, data preparation, and experimentation workflows.
- Familiarity with ML and GenAI frameworks such as PyTorch, TensorFlow, Hugging Face, or OpenAI APIs.
- Some experience working with structured and unstructured datasets (e.g., tabular data, text, JSON).
- Proficiency in Python and version control (e.g., Git); comfort with Jupyter, VSCode, or similar environments.
- Curiosity about GenAI, retrieval-augmented generation (RAG), and product applications of AI in SaaS platforms.
- Strong analytical and communication skills; ability to translate business problems into actionable data tasks.
