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Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.The AI and Infrastructure team is redefining whats possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
Responsibilities
Define, develop and execute post-silicon validation content on both pre-silicon setups and real silicon platforms in the lab.
Drive silicon from being a chip towards becoming a product.
Debug and investigate issues along cross-functional teams such as Firmware, Software, Design, Design Verification (DV), Architecture and multiple production teams.
Provide a quality functional coverage for Google designs.
Design, implement, and maintain validation tests using scripting and programming languages (e.g., Python, C/C++) to verify SmartNIC functionality and performance.

Join our team working on an advanced ad-serving platform that powers millions of real-time interactions every second. As a Senior Backend Developer, youll play a key role in designing, developing, and maintaining a high-performance system that supports critical functionalities like targeting, attribution, budget management, and data pipelines for machine learning and reporting.Youll be expected to lead impactful projects, drive improvements in performance, scalability, and system reliability, and help shape solutions that directly influence the success of a globally recognized platform. We value bottom-up initiatives and encourage team members to bring their ideas to the table, fostering innovation and collaboration.
Why You'll Love This Role:

Take ownership of major projects and core features with significant business impact.
Work alongside skilled engineers in a fast-paced, high-scale environment.
Tackle challenging technical problems using cutting-edge tools like Kafka and Aerospike.
What you'll be doing
Design, develop, and monitor new features for the platform, including components supporting targeting, attribution, and budget management.
Maintain and optimize the performance of critical backend systems.
Refactor and improve legacy code to ensure scalability and efficiency.
Lead efforts to guarantee system reliability and low latency in a high-concurrency environment.
Collaborate with peers and across teams to deliver high-quality, production-ready solutions.

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.

Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

Our mission is to provide the simplest, fastest, and most reliable path for enterprises to migrate their workloads to Google Cloud, accelerating their digital transformation journey. The team has adopted an AI-first approach, where product features and engineering productivity are centered around AI to increase delivery speed and open new opportunities for product journeys.

The AI and Infrastructure team is redefining whats possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Responsibilities
Lead, mentor, and cultivate a high-performing engineering team. Foster a culture of innovation, psychological safety, and continuous career growth for every team member.
Oversee the team's execution and project life-cycle, ensuring the timely and efficient delivery of high-quality, scalable features in a changing, agile environment.
Advocate a customer-first culture by instilling the highest standards for service reliability, performance, and quality.
Drive our AI-first strategy's evolution from both a management perspective, inspiring the team and a technical one, guiding the practical integration of AI into both our product and our internal development processes.
Resolve technical problems inherent in a large-scale, enterprise-grade migrat

Unity LevelPlay is a leading mediation platform that empowers app developers to optimize ad revenue by seamlessly connecting their apps to multiple ad networks.
At the core of LevelPlay, the LevelPlay Infra team is responsible for the mission-critical, real-time in-app bidding system, which serves billions of ad auction requests per day.

We are looking for an experienced and passionate Staff Backend Software Engineer

to join a rapidly growing team. In this role, you will lead the design and evolution of our large-scale, real-time infrastructure that powers global in-app advertising.

Youll tackle complex engineering challenges and drive the design of systems built for massive scale, reliability, and performance. As a hands-on technical leader, youll influence architecture and implementation decisions that define the future of LevelPlays infrastructure.

This is a great opportunity for experienced professionals who have a strong background in backend development and a deep understanding of large-scale distributed systems. If you're passionate about tackling complex technical challenges and building products that reach a massive global audience, this role is for you.

What you'll be doing
Lead the design and development of large-scale, low-latency, high-throughput systems that power real-time ad bidding and delivery.
Define and drive technical strategy and long-term architecture for LevelPlays core infrastructure.
Collaborate cross-functionally with product, data, and ad network integration teams to deliver impactful solutions that scale globally.
Mentor and guide engineers, fostering a culture of technical excellence, ownership, and continuous improvement.
Investigate and resolve complex system challenges, optimizing performance, reliability, and cost efficiency.

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.

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
As a Design Verification Engineer, you will work as part of a Research and Development team building verification components, constrained-random testing, system testing, and verification closure. As part of our server chip design team, you will verify digital designs. You will collaborate with design and verification engineers in active projects and perform verification. You will be responsible for the full life-cycle of verification which can range from verification planning, test execution or collecting and closing coverage.

The AI and Infrastructure team is redefining whats possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

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 or formally verify designs with SystemVerilog Assertions (SVA) and industry leading formal tools.
Identify and write all types of coverage measures for stimulus and corner-cases.
Debug tests with design engineers to deliver functionally correct design blocks.
Apply close coverage measures to identify verification holes and to show progress towards tape-out.