The Applied Research team is a group of data scientists and content specialists who are experts in leveraging machine learning models, natural language processing and generative AI to develop solutions which deliver value to our users and business.
We act as a key driver for innovation, whether it’s in product surface experimentation, metadata generation or model development. Along with Product and Engineering partners, we design solutions and collaborate in cross-functional squads to maximize business impact.
Our areas of impact include representation learning, recommendations, search, translation and many others, applied to diverse media across audio, image and text. We operate at a scale of hundreds of millions of documents, millions of users and billions of user interactions.
About You
- Genuinely have a love for books and enjoy reading
- Are a curious individual who enjoys exploring data and finding meaning behind its patterns
- Have a collaborative spirit and enjoy sharing knowledge with your colleagues
- Have an eye for impact and are excited to build models that will affect millions of users
Responsibilities
- In your first year, you’ll be focusing on a variety of content classification use cases, leveraging everything from traditional NLP to sophisticated fine tuning of LLMs
- Investigate methods of solving our most challenging problems at Scribd, at scale
- Work with other Data Scientists and Machine Learning Engineers to operationalize data science projects
- Leverage any algorithm at your disposal: from classical Scikit-learn and NumPy models to custom Neural Networks in PyTorch to third party LLM APIs
- Process massive amounts of data with Python, SQL and Spark
- Educate stakeholders through written and verbal communications methods on the approaches and results of projects, while writing detailed, accurate and concise project write ups
Requirements
- 2-3 years of experience of developing and deploying machine learning models
- Intermediate level or greater experience with SQL or Spark
- Intermediate to advanced knowledge with Python
- Intermediate level in at least three of these fields: classification algorithms, natural language processing, search, information retrieval, named entity recognition, deep learning, computer vision, bayesian statistics or frequentist statistics
- A keen interest in learning what’s necessary to solve a business problem and make a positive business impact.
- Bachelors or Masters in relevant quantitative discipline (e.g. Computer Science, Software Engineering, Data Science, Machine Learning, Artificial Intelligence, Computational Linguistics, Mathematics, Statistics, Economics)
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 $121,000 [minimum salary in our lowest geographic market within California] to $196,250 [maximum salary in our highest geographic market within California].
In the United States, outside of California, the reasonably expected salary range is between $100,000 [minimum salary in our lowest US geographic market outside of California] to $186,500 [maximum salary in our highest US geographic market outside of California].
In Canada, the reasonably expected salary range is between $125,500 CAD[minimum salary in our lowest geographic market] to $186,000 CAD[maximum salary in our highest geographic market].
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