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Tier-1 brand, popular SDE title, metro location, mid-level experience, and broad required skills increase competition.
Core cloud, data engineering, and MLOps skills are broadly transferable despite advertising-bidding domain experience.
Explicit 2+ years and required cloud, Kubernetes, and data-stack skills make shortlisting moderately strict.
Develop and maintain production-grade software components for high-scale ML systems for Meta/SEM bidding, including data pipelines and backend services.
Collaborate with ML engineers to operationalize experimental ML workflows into robust, monitored production systems (batch and streaming).
Ensure reliability and observability by participating in code reviews, incident response, on-call rotations, and instrumentation to capture operational metrics.
2+ years professional experience building and shipping production software, preferably data-intensive backend services in cloud/hybrid environments.
Bachelor's degree in Computer Science or related technical field or equivalent professional experience.
Proficient in Python with experience building APIs/services (FastAPI, REST) and strong fundamentals in data structures, algorithms, testing, and version control.
Experience with AWS cloud services, container orchestration with Kubernetes, and familiarity with big data frameworks (Go, Spark/Scala/PySpark) and databases (Hive, Iceberg, Postgres).
Experienced in building scalable distributed systems integrating ML workflows in production environments.
Comfortable working with diverse data engineering tools and MLOps practices, showing curiosity to grow in data/ML engineering.
Demonstrates strong problem-solving skills and uses AI-assisted software development tools as part of daily engineering work.