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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.

Technical Leadership & Architecture: Drive data infrastructure strategy and establish standardized patterns for AI/ML workloads, with direct influence on architectural decisions across data and engineering teams
DataOps Excellence: Create seamless developer experience through self-service capabilities while significantly improving data engineer productivity and pipeline reliability metrics
Cross-Functional Innovation: Lead collaboration between DevOps, Data Engineering, and ML Operations teams to unify our approach to infrastructure as code and orchestration platforms
Technology Breadth & Growth: Work across the full DataOps spectrum from pipeline orchestration to AI/ML infrastructure, with clear advancement opportunities as a senior infrastructure engineer
Strategic Business Impact: Build scalable analytics capabilities that provide direct line of sight between your infrastructure work and business outcomes through reliable, cutting-edge data solutions
What you'll be doing
Design Data-Native Cloud Solutions - Design and implement scalable data infrastructure across multiple environments using Kubernetes, orchestration platforms, and IaC to power our AI, ML, and analytics ecosystem
Define DataOps Technical Strategy - Shape the technical vision and roadmap for our data infrastructure capabilities, aligning DevOps, Data Engineering, and ML teams around common patterns and practices
Accelerate Data Engineer Experience - Spearhead improvements to data pipeline deployment, monitoring tools, and self-service capabilities that empower data teams to deliver insights faster with higher reliability
Engineer Robust Data Platforms - Build and optimize infrastructure that supports diverse data workloads from real-time streaming to batch processing, ensuring performance and cost-effectiveness for critical analytics systems
Drive DataOps Excellence - Collaborate with engineering leaders across data teams, champion modern infrastructure practices, and mentor team members to elevate how we build, deploy, and operate data systems at scale