Design and manage end-to-end data workflows to support the ML engineering lifecycle, focusing on preparing data for model training, tracking data lineage, evolving schemas to adapt to changing needs, and ensuring data integrity and reliability in production.
Build and optimize real-time serving systems to deliver low-latency, high-throughput APIs for model predictions and personalized recommendations, ensuring reliable and scalable performance in production environments.
Collaborate with other product engineers and cross-functional partners to develop new Host pricing functionality and surface model recommendations, insights and analytics
Contribute to the development of long-term ML Infra and Data workflow strategies and roadmaps and ML infrastructure development within the host pricing organization.
Mentor and coach team members, providing guidance in ML infra and data engineering best practices and support to enhance their skills and performance.
Ability to work in areas outside of your usual comfort zone and show motivation for personal growth
Your expertise
10+ years of experience with a BS/Masters or 6+ years with a PhD
Experience leading and shipping large scope technical projects in collaboration with multiple experienced engineers.
You are a full-cycle developer: strong ownership and experience building and operating high-scale, distributed systems across the full software life cycle.
You have excellent communication skills and the ability to work well within a team and across engineering teams.
Expertise in large-scale distributed data processing frameworks like Presto or Spark.
Prior experience with the whole lifecycle of productionalization of ML models, including ETL pipelines for data training, feature generation, model evaluation and real-time serving.
You are a strong problem solver and have solid production debugging skills.