About the RoleThe Director, AI/ML Platform Engineering leads the engineering vision and execution for Priceline's AI/ML Platform, the unified infrastructure that enables model development, deployment, orchestration, and productionization at scale. The role defines and executes the technical strategy for MLOps, model serving, feature engineering, experimentation, LLM orchestration, and agentic AI workflows. It is a hybrid work model: two days in-office.ResponsibilitiesDefine and execute the technical strategy for the AI/ML Platform.Lead multiple global engineering teams building highly available, scalable ML infrastructure serving hundreds of models.Architect and evolve end‑to‑end MLOps pipelines including data versioning, feature stores, model training, evaluation, deployment, monitoring, and retraining automation.Build and scale LLM infrastructure for prompt management, retrieval‑augmented generation, fine‑tuning pipelines, evaluation frameworks, and cost optimization.Drive adoption of Model Context Protocol (MCP) and agentic frameworks to enable intelligent, context‑aware applications.Collaborate closely with data science, ML engineering, product, and platform teams to deliver self‑service tools that accelerate model development and reduce time‑to‑production.Champion ML observability, governance, compliance and responsible AI practices ensuring models are explainable, fair, performant and privacy‑compliant.Drive engineering excellence through automation, CI/CD for ML, infrastructure‑as‑code, and platform reliability engineering.Mentor, coach and grow talent within distributed engineering teams.Engage with leadership and stakeholders to align platform priorities with business objectives and AI strategy.Qualifications10+ years of experience in software, platform,



or ML engineering, with 5+ years leading teams that build large‑scale AI/ML platforms or MLOps infrastructure.Proven expertise in MLOps and ML infrastructure: model training orchestration, feature stores, model registries, serving infrastructure, A/B testing, monitoring and observability.Hands‑on experience with Vertex AI, Kubeflow, MLflow or equivalent; and with LLM tooling such as LangChain or LlamaIndex, vector databases, and prompt engineering frameworks.Deep understanding of LLM operations: fine‑tuning, embeddings, RAG architectures, inference optimization, cost management and evaluation frameworks.Familiarity with Model Context Protocol (MCP) or similar standards, or strong ability to drive adoption of emerging AI infrastructure patterns.Strong cloud and data platform skills (GCP preferred): BigQuery, Dataflow, Dataproc, GKE, Cloud Run, Pub/Sub, Airflow/Composer, dbt, Spark, Kafka.Experience with ML governance: model versioning, lineage tracking, bias detection, explainability, privacy‑preserving ML and compliance (GDPR, CCPA, AI regulations).Excellent collaborator who thrives in cross‑functional environments and can translate complex platform capabilities into business value.Strategic thinker able to balance long‑term platform vision with near‑term delivery.Passion for platform engineering and building tools that make engineers ten‑fold more productive.Advantages & CompensationSalary range: CAD $170,000 to $200,000. Eligible for an annual bonus and/or equity grant. Hybrid work model—two days in‑office, remainder remote.Health and wellness coverage, generous paid time off, work/life support, financial security programs, travel perks, and a people‑first culture. Priceline is a proud equal‑opportunity employer.#J-18808-Ljbffr

📌 Director, Ai/Ml Platform Engineering - C$170,000 - C$200,000 A Year (Winnipeg)
🏢 Priceline
📍 Winnipeg