Principal Machine Learning Engineer, Performance DSP

6 days ago


Pune, Maharashtra, India PubMatic Full time

Company Description: PubMatic (Nasdaq: PUBM) is an independent technology company maximizing customer value by delivering the digital advertising supply chain of the future. PubMatic's sell-side platform empowers the world's leading digital content creators across the open internet to control access to their inventory and increase monetization by enabling marketers to drive return on investment and reach addressable audiences across ad formats and devices. Since 2006, our infrastructure-driven approach has allowed for the efficient processing and utilization of data in real time. By delivering scalable and flexible programmatic innovation, we improve outcomes for our customers while championing a vibrant and transparent digital advertising supply chain. Job Description We are immediately hiring a results-oriented Principal Machine Learning Engineer, Performance DSP, to join our growing team in Pune on a hybrid schedule. Reporting to the Director of Machine Learning, you will partner with Product and Engineering teams to both solve problems and identify new opportunities for the business. The ideal candidate will apply quantitative analysis, modeling, and data mining to help drive informed product decisions for PubMatic + get things done. Role and Responsibilities: Assess our existing products to identify inefficiencies across platforms for Performance DSP. Work closely with product, CTO, and engineering teams to align technical solutions for Performance DSP goals. Architect and develop solutions to bridge gaps in technology and execution. Collaborate with product, engineering, and leadership teams to align on DSP strategy. Improve attribution tracking, user value modeling, and ML-driven performance enhancements. Key Experience and Skills: Extensive knowledge of Performance DSP, including programmatic advertising workflows, RTB, audience targeting, and bid strategies. Strong expertise in Machine Learning and Ad-Server/Bidder architecture. Deep understanding of mobile advertising ecosystems, advertising SDKs, and optimization strategies. Hands-on experience with mobile advertising, optimization techniques, and advanced ML algorithms. 7 to 12 years of hands-on experience designing Machine Learning models to solve business problems with statistical packages, such as R, MATLAB, Python (NumPy, Scikit-learn + Pandas) or MLlib Deep interest and aptitude in data, metrics, analysis, and trends, and applied knowledge of measurement, statistics, and program evaluation Distinctive problem-solving skills and impeccable business judgment Capable of translating analysis results into business recommendations



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