Staff Software Engineer, Feature Platform

About the role

At Unity, we're building a world-class advertising platform that operates at a massive global scale. The Ads team powers the systems that connect advertisers with creators and players, driving performance, reliability, and growth across our ecosystem. As a Staff Software Engineer on the Feature Platform team, you'll play a critical role in building the infrastructure that powers machine learning, experimentation, and optimization across our ads ecosystem. You'll design and operate the systems that transform high-volume event data into production-grade feature datasets used for bidding, attribution, and ranking - working at the intersection of distributed systems, platform engineering, and ML infrastructure. This role goes beyond data processing. You'll own the full software lifecycle of pipeline systems - from architecture and implementation through to reliability, observability, and performance at scale - collaborating closely with ML, backend, and product teams to build durable, high-quality infrastructure that supports both offline training workflows and online feature serving. This role is ideal for someone who enjoys owning complex systems end-to-end, thinking deeply about correctness and scalability, and building software that other engineering teams depend on.

Responsibilities

• Design, build, and operate scalable, production-grade data pipeline systems and curated feature datasets powering ads optimization and ML
• Own end-to-end offline data flows from raw event ingestion to feature-ready datasets, with strong emphasis on correctness, reproducibility, and SLA compliance
• Develop and maintain large-scale batch and streaming systems (Python / Java / SQL) with a strong focus on performance, cost-efficiency, and reliability
• Build and contribute to our Feature Store platform, including integration with the high-throughput online serving layer (Go-based services)
• Translate complex product and monetization logic into well-engineered, extensible systems serving analytics and machine learning use cases
• Drive improvements in observability, testing frameworks, and quality standards across the platform
• Lead architectural decisions and engineering best practices within the Feature Platform team

Requirements

• Strong software engineering fundamentals with deep experience designing and operating large-scale distributed systems in production
• Hands-on experience building production-grade ETL/ELT pipelines using Python, Java, SQL, or similar technologies
• Experience with distributed processing frameworks such as Spark or Flink in both batch and streaming modes, including performance tuning and parallel computation
• Understanding of how offline data systems integrate with online serving layers - feature stores, low-latency APIs, and real-time systems
• Experience with cloud-native environments, containerized systems, Kubernetes, and workflow orchestration tools
• Strong ownership mindset - focused on correctness, observability, and long-term maintainability
• Experience with Go is a plus, particularly for collaboration on high-throughput feature serving services
• You might also have
• Experience with ML infrastructure, feature stores, or model training pipelines
• Background in ads, attribution, or monetization systems
• Familiarity with experimentation and metrics infrastructure
• Exposure to high-scale backend or platform engineering
• Additional information
• Relocation support is not available for this position

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