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Unity iAds is looking for a hands-on data infrastructure and platform engineer with proven leadership skills to lead and evolve our self-service data platform that powers petabyte-scale batch and streaming, near-real-time analytics, experimentation, and the feature platform. Youll guide an already excellent team of senior engineers, own reliability and cost efficiency, and be the focal point for pivotal, company-wide data initiatives- feature platform, lakehouse, and streaming.
Own the lakehouse backbone: Mature Iceberg at high scalepartitioning, compaction, retention, metadataand extend our IcebergManager in-house product to automate the lakehouse management in a self serve fashion.

Unify online/offline for features: Drive Flink adoption and patterns that keep features consistent and low-latency for experimentation and production.

Make self-serve real: Build golden paths, templates, and guardrails so product/analytics/DS engineers can move fast safely.

Run multi-tenant compute efficiently: EMR on EKS powered by Karpenter on Spot instances; right-size Trino/Spark/Druid for performance and cost.

Cross-cloud interoperability: BigQuery + BigLake/Iceberg interop where it makes sense (analytics, experimentation, partnership).

What you'll be doing
Leading a senior Data Platform team: setting clear objectives, unblocking execution, and raising the engineering bar.
Owning SLOs, on-call, incident response, and postmortems for core data services.
Designing and operating EMR on EKS capacity profiles, autoscaling policies, and multi-tenant isolation.
Tuning Trino (memory/spill, CBO, catalogs), Spark/Structured Streaming jobs, and Druid ingestion/compaction for sub-second analytics.
Extending Flink patterns for the feature platform (state backends, checkpointing, watermarks, backfills).
Driving FinOps work: CUR-based attribution, S3 Inventory-driven retention/compaction, Reservations/Savings Plans strategy, OpenCost visibility.
Partnering with product engineering, analytics, and data science & ML engineers on roadmap, schema evolution, and data product SLAs.
Leveling up observability (Prometheus/VictoriaMetrics/Grafana), data quality checks, and platform self-service tooling.

ironSource, part of Unity, is a leading large-scale ad network at the forefront of advertising technology. We are looking for a highly skilled and experienced Senior Software Engineer to join our backend team.
In this role, you will leverage your expertise in distributed systems, data engineering, and software development to design, build, and deploy high-performance solutions. You will take a leading role in developing and maintaining a cutting-edge online machine learning system powered by PyTorch/Tensorflow models and Triton inference server.

This is an opportunity to work on complex, large-scale systems that serve billions of requests, shaping the future of ad tech and ML-driven optimization.

What you'll be doing
Architect and Build: Design, develop, and deploy robust, scalable, and high-performance distributed systems that form the backbone of ironSource's next-generation ML ad network.
Real-Time Ad Serving: Engineer and optimize critical systems for real-time ad serving, enabling machine learning models to make intelligent, low-latency decisions for optimal ad selection.
ML Infrastructure Innovation: Drive the evolution of our ML capabilities by researching, evaluating, and implementing cutting-edge techniques for feature stores, data aggregation, and model serving infrastructure.
Data Pipeline Engineering: Collaborate closely with data scientists and product managers to design, build, and maintain efficient and reliable data lakes and data pipelines, ensuring high-quality data for ML training and analytics.
Operational Excellence: Take ownership of key system components, ensuring their reliability, performance, and scalability in a production environment through proactive monitoring and continuous improvement.

The AI and Infrastructure team works on the worlds toughest problems, redefining whats possible and the possible easy. We empower Google customers by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Googler Cloud customers, and billions of Google users worldwide. Were at the center of amazing work at Google by being the flywheel that enables our advanced AI models, delivers computing power across global services, and offers platforms that developers use to build services.

In AI and Infrastructure, we shape the future of hyperscale computing by inventing and creating world-leading future technology, and drive global impact by contributing to Google infrastructure, from software to hardware (including building Vertex AI for Google Cloud). We work on complex technologies at a global scale with key players in the AI and systems space. Join a team of talented individuals who not only work together to keep data centers operating efficiently but also create a legacy of driving innovation by building some of the most complex systems technologies.


Responsibilities
Plan the verification of digital design blocks by fully understanding the design specification and interacting with design engineers to identify important verification scenarios.
Create and enhance constrained-random verification environments using SystemVerilog and UVM, or formally verify designs with SVA and industry leading formal tools.
Identify and write all types of coverage measures for corner-cases.
Debug tests with design engineers to deliver functionally correct design blocks.
Close coverage measures to identify verification holes and to show progress towards tape-out.