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Join a high-impact team of applied researchers and engineers where you'll dive deep into the full ML lifecyclefrom comprehensive data exploration to model evaluation and performance analysis. This role offers unique exposure to cutting edge machine learning applications while building your expertise in both analytical depth and ML systems.
What you'll be doing
Conduct comprehensive exploratory data analysis and deep-dive investigations across our full data ecosystem to uncover insights that drive ML and product strategy
Analyze ML model results, performance metrics, and conduct sophisticated model evaluations that inform algorithmic improvements
Design, implement, and analyze A/B tests while serving as a key contributor to our model evaluation and experimentation processes
Build analytical pipelines and automated systems that scale our ability to measure ML effectiveness and business impact
Create advanced dashboards and reporting systems that translate complex model performance into actionable business insights

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.