Tech Stack

Description

You will lead the development and operation of ML data infrastructure, managing a team of engineers while defining technical strategy, architecting scalable systems, and collaborating with ML teams to accelerate development cycles.

Requirements

• Bachelor's degree in Computer Science or related field
• 8+ years software engineering experience with large-scale data systems, distributed systems, or ML infrastructure
• 3+ years 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 and drive technical roadmap and long-term strategy for ML Data Service platform
• Architect highly scalable, fault-tolerant systems for data ingestion, transformation, and serving
• Lead technical vision for diverse training data sources, including drive logs and labeling pipelines
• Drive implementation of data quality monitoring, lineage tracking, and governance compliance
• Manage team of engineers, including performance reviews, career development, and mentorship