AI/ML Engineer I

Scope

Translate business goals into measurable ML goals (KPIs, acceptance thresholds) in collaboration with PMs and data scientists.

Own the full lifecycle from prototyping (incl. deep learning and GenAI) to deployment and monitoring.

Develop and maintain observability dashboards and alerts tied to ML metrics and feature drift.

Run and safeguard models in real time

Pilot new ML tools/frameworks, leading integration into production where appropriate.

Act as a cross-org ML thought leader—aligning product, infra, legal, and UX on responsible ML.

Key Deliverables by Level

Level

Title

Key Deliverables

Level 1

AI/ML Engineer I

Cleaned, annotated, and pre-processed datasets for supervised learning models

Simple machine learning models (e.g., logistic regression, decision trees) implemented under guidance

Exploratory data analysis reports

Jupyter notebooks documenting model experiments

Unit...