Staff ML Infra Engineer

Responsibilities

• Drive the end-to-end data platform and data-quality roadmap for Search & Discovery machine-learning initiatives.
• Own and optimize core data logging, processing, and ML model-training pipelines.
• Develop and scale infrastructure for batch and real-time data processing, monitoring, and debugging of ML experiments.
• Design and implement scalable ML-based ranking systems and online ML inference services.
• Collaborate with data scientists, analysts, product managers, indexing platform engineers, ranking engineers, and data platform engineers.
• Research technical approaches for difficult development and integration problems and coach and mentor other engineers.

Requirements

• Bachelor’s degree in computer science, electrical engineering, mathematics, statistics, or a closely related field.
• At least five years of professional experience in applied machine learning.
• Experience with machine learning, deep learning, and statistical modeling.
• Proficiency in Python and/or Java and experience building production-grade ML systems.
• Strong computer science fundamentals, including data structures, algorithms, performance complexity, and computer-architecture impacts on software performance.
• Experience with big data tools, ETL frameworks, scalable data pipelines, mission-critical high-throughput and low-latency services, and cloud technologies such as AWS and GCP.
• Preferred experience with Hadoop, Hive, Presto, Spark, Scala, Apache Airflow, TensorFlow, and PyTorch.
• Strong verbal and written communication skills, including presenting complex technical concepts to non-technical users.
• Experience with machine-learning platforms for search and discovery rankings is a strong plus.

Benefits

• Medical, dental, vision, life, AD&D, disability, FSA, HSA, and EAP benefits.
• 401(k) plan with company match.
• 18–21 days of paid time off annually based on tenure and 12 public holidays.
• Paid parental leave and pre-tax commuter benefits.
• Free electric-car charging station.
• US geographic-market compensation and benefits; the posting lists an application process of phone interview followed by onsite or virtual onsite interview.