Tech Stack

Description

You will lead the development and operation of our core machine learning data infrastructure, ensuring reliable, high-quality data for all ML use cases. You'll define the technical roadmap, architect scalable systems, manage a team of engineers, and collaborate with ML teams to accelerate development cycles.

Requirements

• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience
• 8+ years experience in software engineering with focus on large-scale data systems, distributed systems, or ML infrastructure
• 3+ years experience managing engineering projects with track record of delivering efficient tools and infrastructure
• Deep expertise in data processing technologies (e.g., Spark, Flink, Beam) and cloud platforms (e.g., AWS, GCP, Azure)
• Experience designing and operating production-grade ML data pipelines or feature stores

Responsibilities

• Define technical roadmap and long-term strategy for ML Data Service platform
• Architect complex, scalable, fault-tolerant systems for data ingestion, transformation, and serving
• Lead provision of diverse training data from real-world logs, simulation, auto-labeling, and human labeling
• Implement mechanisms for data quality monitoring, lineage tracking, and governance
• Manage a team of software engineers including performance reviews, career development, and mentoring