- Company Name
- Restaurant Brands International
- Job Title
- Principal Software Engineer - AI/ML
- Job Description
-
**Job Title:** Principal Software Engineer – AI/ML
**Role Summary:**
Design, build, and operationalize end‑to‑end data and machine‑learning infrastructure that powers enterprise forecasting, AI-driven insights, and semantic layers. Own data pipelines, feature stores, and evaluation frameworks, ensuring outputs are governed, explainable, and anchored to authoritative data sources.
**Expectations:**
- Lead the architecture of scalable ML and forecasting systems across sales, labor, inventory, and other operational domains.
- Deliver production‑grade components that integrate seamlessly with the organization’s data ecosystem.
- Champion governance, quality, and security across data and predictive workflows.
**Key Responsibilities:**
1. **Forecasting & ML Engineering**
- Design and implement enterprise forecasting pipelines and feature layers for multiple predictive domains.
- Build reusable ML components, versioned pipelines, experimentation scaffolding, and automated drift detection.
- Ensure predictions are governed, explainable, and linked to source‑of‑truth data with full lineage.
2. **Data & Platform Engineering**
- Onboard, transform, and model enterprise data in Snowflake for ML, forecasting, and analytics.
- Design high‑performance batch and real‑time data models; optimize for scalability and permissioning.
3. **Semantic & AI Layer Enablement**
- Develop governed semantic models and metric definitions to support natural‑language access to insights.
- Provide clean, well‑structured datasets and metadata for AI tools such as Cortex.
4. **Governance, Quality & Trust**
- Implement RBAC, documentation, and audit trails for data and predictive outputs.
- Build evaluation datasets and regression tests to detect drift and maintain performance.
5. **Cross‑Functional Collaboration**
- Translate business requirements from Finance, Operations, Marketing, Technology, and Product into scalable, ML‑ready data assets.
- Advocate for best‑practice data and model architecture to accelerate enterprise AI adoption.
**Required Skills:**
- 5+ years of production data or analytics engineering, with strong Snowflake or equivalent cloud warehouse experience.
- Expert SQL and advanced data modeling (star/snowflake schemas, semantic modeling, metadata).
- Proficient in Python; experience operationalizing ML workloads (pipelines, feature stores, drift detection).
- Knowledge of machine‑learning best practices for time‑series and predictive analytics.
- Hands‑on experience with data governance, RBAC, and compliance (PII handling).
- Familiarity with semantic layers, natural‑language processing, and AI evaluation frameworks.
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Statistics, or a related technical discipline.
- Relevant certifications may include Snowflake Practitioner, Google Cloud Data Engineer, or equivalent advanced data‑engineering credentials.