Conviva is the first and best place to understand and optimize digital customer experiences. Our Operational Data Platform harnesses full-census, comprehensive client-side telemetry—capturing every aspect of customer experience and engagement across all devices and linking them to the performance of underlying services, in real-time and at a fraction of the cost of alternative solutions. Conviva computes quality of experience across all users and all devices, in real time. We combine user actions with app and system responses to give your technology, business, and operations teams AI-powered insights into any issues impacting user experience and engagement. Trusted by industry leaders like Disney, NBC, and the NFL, Conviva revolutionizes how businesses understand customer experience and engagement, maximizing satisfaction, conversion, and revenue.
As a Machine Learning Engineer, you will play a key role in advancing our AI initiatives and contributing to the development of our Real-Time Performance Analytics Platform. You will work across a broad range of ML technologies to create innovative, customer-focused solutions.
In this role, you’ll collaborate closely with vertical product teams to design and deploy ML models directly within product pipelines. You’ll work with other team members to build scalable ML tooling and infrastructure, combining research, product integration, and data development.
What Success Will Look Like:
Who You Are and What You've Done:
What Would Make You Stand Out (Bonus Points):
The expected salary range for this full-time position is $180,000 - $200,000 + equity + benefits. The actual level and compensation are determined by several factors, such as your qualifications, professional background, and relevant experience.
Privately held, Conviva is headquartered in Silicon Valley, California with offices and people around the globe. For more information, visit us at www.conviva.com. Join us to help extend our leadership position in big data streaming analytics to new audiences and markets!
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