Staff Software Engineer, Feature Platform

Unity Technologies•Mountain View, CA

About The Position

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.

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

Nice To Haves

Experience with Go is a plus, particularly for collaboration on high-throughput feature serving services
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

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