Verve Group is hiring a

Backend Staff Engineer - Pune

Pune, India

Who We Are

Verve has created a more efficient and privacy-focused way to buy and monetize advertising. Verve is an ecosystem of demand and supply technologies fusing data, media, and technology together to deliver results and growth to both advertisers and publishers–no matter the screen or location, no matter who, what, or where a customer is. With 30 offices across the globe and with an eye on servicing forward-thinking advertising customers, Verve’s solutions are trusted by more than 90 of the United States’ top 100 advertisers, 4,000 publishers globally, and the world’s top demand-side platforms. Learn more at www.verve.com.

As Verve Marketplace brings the capabilities of all players in the AdTech ecosystem (SSPs & Exchanges) under one umbrella alongside synergies with our in-house DSPs & DMPs, our Data Science R&D currently pursue the following major tracks covering different aspects:

  • Exchange-focused — which includes optimizing the flow of traffic between supply and demand partners and maximizing value for our partners.

  • Audience-focused — which includes enriching bid stream with audiences for targeting and market research in collaboration with our inhouse DMP & DSPs

Who You Are

We are currently seeking a Backend Staff Engineer to join our growing team. Our Backend Staff Engineer role includes research, design, development, and maintenance of our AI platform for exchange optimization, spanning several technologies. This role would be based in our Pune, India office.


What You Will Do

  • Designing, developing, and researching cutting-edge end-to-end Machine Learning Systems with real-time feedback, across our programmatic stack — covering Go, Java & Python.
  • Collaborate with platform/runtime backend team(s) to provide experimental interfaces for testing and development of online approaches
  • Focusing on scalable operations with automation: Supervised — Human Assisted Frameworks; Unsupervised — Self Learning Policy Driven Frameworks
  • Owning and maintaining ETL processes to leverage/extract/process/evaluate complex, high volume, high-dimensional datasets independently or in collaboration with our data platform teams
  • Providing custom datasets curated for specific research purposes from production event flow
  • Developing a Machine Learning Platform supporting our optimization needs
  • Bring data science prototypes to production
  • Supporting, maintaining, and enriching existing ML frameworks and libraries
  • Contribute to reducing business problems into optimization problems by assessing technical feasibility and operational constraints
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