Scribd
San Francisco
201-500 employees
The best audiobooks, books, and more, available anywhere. Join us on our mission to change the way the world reads.
Machine Learning Engineer I
Machine Learning Engineer I
This job is no longer open
At Scribd (pronounced “scribbed”), we believe reading is more important than ever. Join our cast of characters as we work to change the way the world reads by building the world’s largest and most fascinating digital library: giving subscribers access to a growing collection of ebooks, audiobooks, magazines, documents, Scribd Originals, and more. In addition to works from major publishers and top authors, our community includes over 1.9 M subscribers in nearly every country worldwide.
Have you heard about our future of work program, Scribd Flex? As a key principle, we embrace flexibility and allow employees, in partnership with their manager, to choose the work-style that best suits their individual needs and preferences. And, we create intentional in-person moments with each other that build culture and connection.
The Opportunity
We are looking for exceptional, results-oriented, and passionate Machine Learning experts to join our growing Machine Learning Team. As an early member of a world-class team, you will help break ground by creating and owning the next generation of machine learning algorithms and end-to-end systems that power the experience for our 6B+ monthly recommendations and 100M+ users around the world.
Qualifications
• 2+ years of experience applying Machine Learning in the industry, preferably in recommendations and search domains
• Any experience related to using ML infrastructure at scale (Feature Store, Embedding based Retrieval) is a plus
• Strong background in Machine Learning, with knowledge of retrieval and ranking (leveraging deep learning, reinforcement learning, contextual multi-armed bandits)
• Great coding skills and software development experience (preferably in Spark, Scala, Python, Go, and Tensorflow)
• Demonstrated ability in building scalable data and ML pipelines (preferably Airflow, Verta)
• BS in Computer Science, Statistics, or related field
If you are results-oriented, self-driven, motivated to succeed, and are eager to make an impact by working on cutting-edge ML products and shaping Scribd's future, please reach out to us. We are looking forward to talking to you!
Benefits, Perks, and Wellbeing at Scribd
*Benefits/perks listed may vary depending on the nature of your employment with Scribd and the geographical location where you work.
• Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
• 12 weeks paid parental leave
• Short-term/long-term disability plans
• 401k/RSP matching
• Tuition Reimbursement
• Learning & Development programs
• Quarterly stipend for Wellness, Connectivity & Comfort
• Mental Health support & resources
• Free subscription to Scribd + gift memberships for friends & family
• Referral Bonuses
• Book Benefit
• Sabbaticals
• Company wide events
• Team engagement budgets
• Vacation & Personal Days
• Paid Holidays (+ winter break)
• Flexible Sick Time
• Volunteer Day
• Company-wide Diversity, Equity, & Inclusion programs
Want to learn more about life at Scribd? www.linkedin.com/company/scribd/life
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We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing accommodations@scribd.com about the need for adjustments at any point in the interview process.
Scribd is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.
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Remote employees must have their primary residence in: Arizona, California, Colorado, Connecticut, Delaware, DC, Florida, Hawaii, Iowa, Massachusetts, Michigan, Missouri, Nevada, New Jersey, New York, Ohio, Oregon, Tennessee, Texas, Utah, Vermont, Washington, Ontario (Canada), British Columbia (Canada), or Mexico. *This list may not be complete or accurate, and candidates should speak with their recruiter about their specific location for remote work.
#LI-Remote
This job is no longer open