Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

The Data Engineer will work with various teams to develop high-quality datasets, build scalable ETL pipelines, manage data warehousing solutions, and implement data security practices while ensuring data integrity and quality through testing.

The Principal Machine Learning Engineer will drive the technical roadmap for Snap's Ad Marketplace, designing and optimizing machine learning models and systems for efficient ad delivery. Responsibilities include collaborating with teams on machine learning strategies, staying current with technology trends, and mentoring within the ML community.

Lead a team of machine learning engineers in developing a personalized video recommendation engine, ensuring scalability and reliability. Conduct A/B testing, perform design reviews, and collaborate with stakeholders to optimize the recommender system.

As a Product Manager for Ad Formats at Snap Inc, you will lead the vision and strategy for ad formats, prioritize interactions with ads, analyze product metrics, and collaborate with cross-functional teams to develop and launch products that enhance user experiences and provide value to advertising clients.

As an Application Engineer at Snap Inc, you will design and build scalable applications using Force.com, collaborate with product managers to understand business challenges, maintain high application uptime, and produce technical documentation to enhance CRM engineering practices.

The Staff Software Engineer will lead the development and optimization of large-scale content delivery and recommendation systems. This includes the design and implementation of various components such as indexing, retrieval, and online machine learning systems while coaching team members and collaborating with cross-functional partners.

As a Staff Software Engineer at Snap Inc., you will lead the ML Feature Generation team, drive technical direction to enhance machine learning iteration speed, identify improvement opportunities in big data and ML infrastructure, and mentor team members on developing new ML platform capabilities and system efficiencies.