Lead Machine Learning Features Developer
1 week ago
This is a position for an experienced Machine Learning Engineer who will join our team within the Machine Learning Platform.
The successful candidate will help scale high-demand ML feature pipelines and services to meet the needs of teams across various business units, contributing to designing and developing a groundbreaking new ML feature system that aims to redefine how Machine Learning features are computed and delivered at scale.
Key responsibilities include maintaining mission-critical ML feature computation and serving systems, partnering with Data Scientists, ML Modelers, and Software Engineers to deliver reliable, performant, and scalable systems, driving architectural decisions, system reliability improvements, and infrastructure automation, mentoring and guiding other engineers on best practices in large-scale distributed systems, feature engineering, and ML infrastructure, and championing engineering excellence through code reviews, technical documentation, and continuous improvement.
To be considered, candidates should have 5+ years of experience in software engineering, with at least 3+ years in large-scale data or ML infrastructure, strong proficiency in programming languages such as Java, Python, Kotlin, or Go, experience building and operating distributed data systems at scale (e.g., Spark, Flink, Kafka, Databricks, Snowflake), proven ability to design for high performance, scalability, and reliability, deep knowledge of cloud infrastructure (AWS, GCP) and containerized systems (Kubernetes, Docker), and strong collaboration skills and ability to work cross-functionally with ML practitioners and infrastructure engineers.
Candidates with experience in ML workflows, platforms, and systems, building or maintaining ML batch or real-time feature systems, MLOps, experimentation platforms, or ML observability, may also be considered.
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