Machine Learning Engineer

Job Description:

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This is a role for someone who wants to solve hard machine learning problems by building production systems that matter. We're looking for a Staff Machine Learning Engineer who loves shipping production ML systems, owning complex technical problems end-to-end, and partnering closely with Product, Data Engineering, and the business to deliver measurable outcomes. This is a deeply hands-on individual contributor role.

You'll spend the majority of your time building, deploying, experimenting with, and improving production machine learning systems, not managing people or operating primarily at the architectural strategy level. If you enjoy taking ownership of difficult ML problems, iterating quickly through experimentation, and seeing your work directly improve revenue, marketplace efficiency, and customer experience, this role is for you. You'll build production ML systems for a business serving 120M+ registered users that has delivered $2B+ in lifetime rewards, powered by a data platform with 50M daily events, 500M daily pipeline records, a 100TB Iceberg lake, and 50 Kafka topics supporting both batch and real-time workflows.

Prodege: A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Blackstone in Q1 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences.

As an organization, we go the extra mile to "Create Rewarding Moments" every day for our partners, consumers, and team. Come join us today!

• Design, build, and operate production machine learning systems from development through deployment
• Production models supporting ranking, recommendations, personalization, rewards optimization, ROAS/LTV prediction, and offer optimization
• Feature engineering, model training pipelines, online inference, experimentation, monitoring, and continuous improvement
• Reliable production ML practices including testing, observability, retraining, and model health
• Technical leadership through code reviews, collaboration, and mentoring less experienced engineers
• Cross-functional partnerships with Product, Data Engineering, Analytics, and Business stakeholders to solve high-impact problems

You'll work on machine learning problems that directly impact revenue, marketplace efficiency, and customer experience.

You'll own production systems—not just models—from experimentation through deployment and optimization.

You'll build on top of a production platform processing 50M daily events, 500M daily pipeline records, and a 100TB Iceberg lake.

You'll join a team with an active experimentation culture, shipping ML improvements that quickly reach production.

You'll have significant ownership while partnering with senior technical leaders to shape the future of ML at Prodege.

You'll work in an engineering culture embracing AI-assisted development to improve productivity and accelerate experimentation.

• Design, build, deploy, and maintain production machine learning systems.
• Develop scalable ML solutions across ranking, recommendation, personalization, rewards optimization, ROAS/LTV prediction, and experimentation.
• Improve feature engineering, model performance, inference latency, and operational reliability.
• Design and analyze offline evaluations and A/B experiments to validate business impact.
• Partner with Data Engineering to build…