AWS, Data Engineering, Data science techniques, DevOps, Large Language Models - LLMs, Machine learning techniques, Python Programming, Ruby on Rails, Scala Programming, Software Development, Terraform
About The Team
Our Machine Learning Platform sits at the heart of an ecosystem with over 200 million pieces of content, more than 200 million unique visitors each month, and empowering 2 million paying subscribers across the globe. With content available in over 20 languages, our platform presents unparalleled opportunities and challenges for AI innovation. This curated developer environment is designed not just to enable, but to accelerate AI projects, fueling an extraordinary Scribd user experience. Our platform supports a wide array of machine learning applications, from sophisticated classifications and personalized recommendations to cutting-edge Large Language Models (LLMs). The ML Platform team is tasked with navigating the complexities of deploying state-of-the-art ML solutions rapidly and cost efficiently. By constructing, delivering, and maintaining a robust platform, we ensure the seamless flow of the entire machine learning workflow — from initial experimentation to final production deployment.
The team is remote-first and is spread across time zones across North America and Europe. We use tools that emphasize asynchronous communication but also pair program or use online meetings when those are the best approaches. Regardless of the medium, excellent communication skills are a must. We operate with autonomy (developers closest to the code will make the most well-informed decisions) while holding ourselves and each other accountable.
About You
You are an experienced engineer looking for a new challenge and embrace learning new things. You have a passion for DevOps and Machine Learning. Solving challenging problems excites you and you don’t mind diving deep but you also know when to reach out to colleagues for help. You are strong at communicating and listening to customers to understand there needs.
About the Role
Minimum Requirements
Desired Skills
At Scribd, your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States. In the state of California, the reasonably expected salary range is between $143,000 [minimum salary in our lowest geographic market within California] to $231,000 [maximum salary in our highest geographic market within California].
In the United States, outside of California, the reasonably expected salary range is between $117,500 [minimum salary in our lowest US geographic market outside of California] to $219,500 [maximum salary in our highest US geographic market outside of California].
In Canada, the reasonably expected salary range is between $147,000 CAD[minimum salary in our lowest geographic market] to $217,750 CAD[maximum salary in our highest geographic market].
We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package.
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.
Want to learn more about life at Scribd? www.linkedin.com/company/scribd/life
Scribd Inc. is an American e-book and audiobook subscription service that includes one million titles. Scribd hosts 60 million documents on its open publishing platform. The company was founded in 2007 by Trip Adler, Jared Friedman, and Tikhon Bernstam, and headquartered in San Francisco, California.