Job Description:
• Design, build, and operate backend services and large-scale data pipelines that power Native Ads forecasting, supply allocation, and campaign delivery optimization.
• Develop and maintain the data infrastructure behind ML forecasting models that predict campaign reach, clicks, conversions, and supply availability across segments, surfaces, and markets.
• Build systems that enable forecasting at scale; supporting bulk buying workflows, multi-subcampaign budget allocation, and high-throughput forecast serving for internal and external customers.
• Contribute to supply optimization systems including campaign pacing, business-aware supply allocation, and auction infrastructure to maximize delivered revenue and yield.
• Collaborate with data scientists and ML engineers to productionize prediction models, build feature pipelines, and ensure model outputs are reliable and observable in production.
• Help drive improvements to data quality, pipeline reliability, and system observability across the forecasting and delivery stack.
• Work in a cross-functional, agile squad alongside product managers, data scientists, and other engineers to continuously experiment, iterate, and deliver on squad objectives.
Requirements:
• 3+ years of professional experience in backend engineering, with meaningful exposure to data engineering or ML infrastructure.
• Proficient in at least one backend language such as Java, Scala, or Python, and have experience building services and data pipelines that operate at scale.
• Experience with distributed data processing frameworks (e.g., Scio, Apache Beam, Spark, Flink, or Dataflow) and are comfortable working with large-volume, heterogeneous datasets.
• Familiarity with cloud data platforms, ideally GCP, including tools like BigQuery, Cloud Storage, Pub/Sub, and Dataflow.
• Understanding of data modeling, pipeline orchestration, and the tradeoffs between batch and streaming architectures.
• Care about data quality, system reliability, and building infrastructure that downstream consumers can trust.
• Excitement to work at the boundary of backend systems and data/ML, eager to deepen skills in both areas.
• Thrive in collaborative, cross-functional environments and comfortable navigating ambiguity as requirements evolve.
• Growth mindset and energized by the prospect of seeing work directly impact how artists promote their music to millions of listeners.
Benefits:
• health insurance
• six month paid parental leave
• 401(k) retirement plan
• monthly meal allowance
• 23 paid days off
• 13 paid flexible holidays