Senior Software Engineer - Applied Data

About the role

About Moloco:

Moloco is an AI-native performance advertising company, bringing the power of AI advertising to the open internet. Founded in 2013 by machine learning engineers who had built AI advertising systems inside the world's largest technology companies, Moloco began from a shared mission: to build that same engine for the open internet.

Today, Moloco is one company with two businesses, built on the same compound AI system. Moloco Ads is our AI-native performance advertising platform, helping mobile app marketers acquire, retain, and re-engage high-value users across the open internet. Moloco Commerce Media is our AI-native retail media platform, enabling retailers and marketplaces to turn their platforms into thriving ad businesses. Both are powered by CARA (Compound Ad Recommendation Architecture), the AI system behind every Moloco product.

At Moloco, we bring together those who've already solved hard problems and those with the drive to. Here, we work on some of the complex problems in AI advertising, at a scale and level of sophistication very few companies can offer. Come build what's next.

About the Role

The Ads Applied Data team builds and scales the foundational data infrastructure that powers Moloco’s advertising platform. As a Senior Software Engineer, you will design, develop, and optimize distributed data systems for real-time and batch processing, ensuring reliable and low-latency delivery of data across the ads ecosystem. You’ll work closely with Product, ML, and Data Science teams to enable feature engineering, identity resolution, and advanced user signal enrichment across online and offline pipelines.

Responsibilities

- Design and build large-scale distributed systems for data ingestion (Petabyte-scale), transformation, and serving.

- Partner with ML and Serving teams to support feature engineering workflows, connecting offline data to serving systems.

- Contribute to the evolution of Feature Infra / Feature Store, ensuring scalability, discoverability, and consistency of feature data.

- Collaborate on Identity Graph construction to unify user and device identifiers for more effective signal enrichment and targeting.

- Improve system observability, resilience, and performance in high-throughput, low-latency environments.

- Mentor engineers and help define best practices for data and backend engineering.

Qualifications

- Bachelor’s or Master’s degree in Computer Science, or equivalent technical field.

- 5+ years of software engineering experience with one or more modern languages (Java, Kotlin, Go, C++, C#, or Python).

- Proven experience designing and building large-scale distributed systems and backend services.

- Hands-on experience with data processing frameworks such as Apache Beam, Dataflow, or Spark, and orchestration tools like Airflow.

- Strong understanding of cloud infrastructure (GCP, AWS, or Azure) and data storage technologies (BigQuery, Bigtable, Redis, GCS, Kafka, Pub/Sub).