Senior Staff Machine Learning Engineer

What you'll do

• Define and drive the technical strategy and roadmap for the Personalization Platform.
• Develop and maintain a scalable rules engine for business-driven personalization logic and user segmentation.
• Build and maintain robust ML infrastructure to support feature extraction, training, evaluation, and deployment.
• Architect low-latency, event-driven systems for real-time decisioning based on streaming data and contextual signals.
• Drive MLOps evolution by building automated metrics-backed deployment workflows and monitoring systems.
• Implement state-of-the-art LLM optimization techniques to improve performance, cost, and latency of production AI systems.
• Provide organizational technical leadership to influence architecture, engineering standards, and cross-team strategies.

What we're looking for

• Bachelor's degree required; Master's or PhD in Computer Science or a related technical field preferred.
• At least 10 years of experience designing and building data-intensive solutions using distributed computing.
• At least 7 years of experience programming in C, C++, Python, or Scala.
• At least 4 years of experience with the full ML development lifecycle in a business-critical setting.
• At least 8 years of experience deploying scalable, responsible AI solutions on major cloud platforms like AWS, GCP, or Azure.
• At least 5 years of expertise in designing and scaling personalization platforms and recommendation systems.
• At least 5 years of experience with ML frameworks (PyTorch, TensorFlow) and orchestration tools (Databricks, Airflow, Kubeflow).
• At least 5 years of experience in cloud-native engineering, containerization (Docker, Kubernetes), and automated CI/CD deployment.