About this role

Translate business goals into measurable ML goals (KPIs, acceptance thresholds)
Own the full lifecycle from prototyping 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
Assist in data cleaning, feature engineering, testing basic ML models, write and debug simple scripts
Develop ML modules, assist in deployment, support data pipelines, contribute to documentation and unit testing

Bachelor’s degree in Computer Science, Data Science, IT, or a related field
1–2 years in data science/ML roles; hands-on with frameworks like scikit-learn or PyTorch
Programming: Python (must), Java/C++ (optional), SQL, Apps Script, ServiceNow
Frameworks: TensorFlow, PyTorch, scikit-learn, HuggingFace
Tools: Git, Docker, Kubernetes, Airflow, MLflow, Jupyter, Postman
Microsoft Office

AI/ML Engineer I

Key skills