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.
Other Open Roles
Prior Listings
Senior Machine Learning Platform Engineer
Senior Machine Learning Platform Engineer
At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. Join our team as we create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our three products: Everand, Scribd, and Slideshare.
We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer.
We love collaborating and investing time in our Scribd community, and we create intentional in-person moments with each other to build culture and connection. And, it is through our flexible work benefit – Scribd Flex – that we enable employees, in partnership with their manager, to choose the work-style that best suits their individual needs and preferences.
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
• Scribd is searching for an Engineer to join the Machine Learning Platform team, you will be a part of designing, implementing and supporting services, tools and infrastructure that makes up the machine learning platform.
• We recognize that everyone has a unique set of work and life experiences, and believe that a broader set of perspectives will produce better results for all. We continually strive for inclusivity and strongly value diversity. We support others' growth and celebrate our collective achievements.
• You will influence the future and direction of Machine Learning at Scribd
Minimum Requirements
• An appetite to learn and grow professionally
• Strong written and verbal communication skills (we're a remote team!)
• You will be communicating directly with the data scientists and engineers using the platform to understand requirements and providing remote support.
• Software development background
• Expertise in programming and software engineering. Ability to read and write code in one or more languages ideally Go, Python, Ruby, and/or Scala code. Strong understanding of software design principles.
• Expertise applying Devops principles and tooling
• Proficiency with common software development processes such as Agile development
• Ability to lead technical design discussions within your team, and across partner teams
• Experience working with infrastructure and a familiarity with Infrastructure best practices
• Mentoring skills: experience with training and educating teammates or colleagues
Desired Skills
• An understanding of AWS platform services
• Concepts of Data Engineering
• Infrastructure as code preferably Terraform
• Experience deploying Machine Learning models in production
• Experience with Machine Learning concepts and fundamentals
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.
• 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, Maryland, 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.
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