PubMatic is one of the world’s leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes.
Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.

JOB DESCRIPTION:

We are looking for a Lead Machine Learning Engineer with deep expertise in Performance advertising and a proven track record of architecting high-performance solutions that drive campaign success. Leveraging your strategic understanding of Performance DSP workflows, you will design cutting-edge algorithms and systems to optimize real-time bidding strategies, exceed advertiser KPIs, and maximize ROI ultimately increasing performance-driven spend on the PubMatic platform.

QUALIFICATIONS:

• 5+ years of engineering experience at a Performance DSP, coupled with a deep understanding of programmatic advertising workflows, RTB, audience targeting, and bid strategies.
• Deep understanding of mobile advertising ecosystems, advertising SDKs, and optimization strategies.
• Strong expertise in Machine Learning, Ad-Server/Bidder architecture and Gen-AI.
• BS or MS degree in Computer Science or Mathematics

• Architect and develop advanced features to shape Performance DSPs, optimizing ad formats such as interstitial video, rewarded video, and display ads.
• Design PubMatic’s product offering to boost auction efficiency and align with Performance DSP workflows and expectations ensuring seamless integration, higher ROI for advertisers, and increase the DSP spend on the platform.
• Leverage machine learning and data-driven insights to enhance bid efficiency, campaign performance, and ad delivery strategies.
• Collaborate with cross-functional teams including Product, Engineering, and the CTO team to align technical solutions with Performance DSP goals.
• Optimize attribution tracking, user value modelling, and ML-driven performance enhancements to maximize campaign impact.