the omnichannel outcomes platform for the open internet, driving full-funnel results for marketers across premium media. With a focus on meaningful business outcomes for branding and performance objectives, the combined company ensures value is driven with every media dollar by leveraging predictive AI technology to connect quality media, beautiful brand creative, and context-driven addressability and measurement. One of the most scaled advertising platforms on the open internet, directly partnered with more than 10,000 publishers and 20,000 advertisers globally. The company is headquartered in New York, with a global team of nearly 1,800 people in 36 countries.
About the opportunity
We are looking for a seasoned engineer who combines strong backend engineering expertise with proven experience in machine learning. You will play a critical role at the intersection of backend systems, data engineering, and ML infrastructure, building scalable platforms and algorithms that power our large-scale ML workflows. Your work will directly impact the performance, reliability, and scalability of our ML systems, from core infrastructure and model deployment to performance monitoring and KPI optimization.
What will you do?
Architect and implement efficient, scalable backend systems for high-performance ML workflows, data processing pipelines, and core infrastructure services.
Develop, adapt, and optimize ML algorithms, contributing to the platforms core ML capabilities and features.
Ensure all systems are tested, observable, and optimized, including automated unit, integration, and load testing for ML workloads.
Optimize infrastructure and algorithms for latency, throughput, and accuracy, tackling production-level challenges in distributed and GPU-enabled environments.
Collaborate closely with data scientists to implement core infrastructure features and integrate them into the ML platform.
Stay up-to-date with emerging ML frameworks, distributed systems technologies, and performance optimization techniques to maintain a cutting-edge platform.
Requirements: 4+ years of professional experience in backend and ML-related engineering roles.
Strong foundation in system design, API development, and performance tuning.
Experience with ML frameworks such as TensorFlow, PyTorch, and related tooling.
Masters in Computer Science, Engineering, or a related technical field is an advantage.
Passion for clean, maintainable, production-grade code with measurable ML impact.
Excellent communication skills and a collaborative mindset across engineering, data science, and product teams.
Bonus Points:
Advanced backend skills with languages including Python, Java, Scala, Go, or Rust.
Experience with cloud infrastructure (AWS, GCP), AWS Batch, S3, and GPU optimization.
Familiarity with Spark, Airflow, BigQuery, and large-scale data pipelines.
Performance engineering expertise: profiling, benchmarking, and tuning ML workloads.
Prior experience building or maintaining ML flows and production pipelines.
This position is open to all candidates.