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 Machine Learning Platform team builds, delivers, and supports the ML Platform a collection of services, infrastructure, tooling and best practices designed to empower our customers to effectively deliver ML solutions that power the Scribd experience. We deliver technologies which enable other teams to build new and better solutions.

The team is remote-first and is spread across time zones across North America and Europe. We use tools that emphasize asynchronous communication but will 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.

Our Machine Learning Platform is a blend of off-the-shelf and developed in-house services and tooling that has been chosen to enable our ML and Data Science customers to deliver solutions and includes a growing list of components such as Model Database, Feature Store and Embedding Based Retrieval. An engineer in the Machine Learning platform will get an opportunity to work on a wide array of technologies and play a pivotal role in designing, implementing, testing, deploying and supporting software, services, tooling and infrastructure.

 

You've learned a lot in the first few years of your software engineering career and now you're ready for the next challenge. You've overcome the typical early-career struggles while learning languages, frameworks, tools, and now are able to be productive in a way that you're proud of. Tasks that used to be hard are now easy. You've become adept at debugging. You also know when to reach out for help, and don't have an ego that would get in the way of doing so. You may have taken on some larger projects, including owning the technical design of your work. You're ready to take the next step, towards greater challenges and more responsibility.

 

•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

•An appetite to learn and grow professionally

•Strong written and verbal communication skills (we're a remote team!)

•Software development background

•Ability to read and write code in one or more languages ideally Go, Python, Ruby, and/or Scala code

•Familiarity with software development principles, ideally the concepts of SOLID

•Familiarity with git

•Ability to write tests

•Familiarity with common software development processes such as Agile development

•Capable of reading and understanding the code in order to participate in the code review process

•Ability to participate in technical design discussions within your team, and across partner teams

•An interest or understanding of Machine Learning

•Experience in some areas of the ML life cycle and concepts of MLOps

•An understanding of AWS platform services

•Concepts of Data Engineering

•Experience with dev ops including CI/CD concepts and tooling

• 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

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Remote employees must have their primary residence in: Arizona, California, 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.