Senior Applied Scientist
2 weeks ago
We are building a holistic team focused on leveraging advances in AI to improve the Reading experience for Kindle customers, and the Publishing experience for book content creators and distributors; and this role is specifically for an Applied Scientist who will focus on making publishers lives easier through AI.
We are building a Publishing & Reading Science team and looking for Scientists, who are passionate about Reading and are willing to take Reading to the next level. Every Book is a complex structure with different entities, layout, format and semantics, with more than 17MM eBooks in our catalog across different publishers. We are looking for experts in all domains like core NLP, Generative AI, CV and Deep Learning Techniques for unlocking capabilities like analysis, enhancement, curation, moderation, translation, transformation and generation in Books based on Content structure, features, Intent, Synthesis and publisher details. Scientists will focus on Inside the book content and semantically learn the different entities to enhance the Reading and publishing experience overall (Kindle & beyond). They have an opportunity to influence in 3 major phases of life-cycle - Publishing (Creation of Books process), Reading experience (building engaging features & representation in the book thereby driving reading engagement) and Reporting (improvement through their sales & business growth).
Key job responsibilities
- Inspect AI initiatives across Amazon to identify how these can be applied and scaled to book publishers or publishing workflows.
- Participate in team design, scoping and prioritization discussions. You must be able to map a business goal to a scientific problem, and map business metrics to technical metrics.
- Spearhead the design and implementation of new features and algorithms based on thorough research and collaboration with cross-functional teams.
- You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning
- You are able to use reasonable assumptions, data, and customer requirements to solve problems.
- You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members.
- You work with SDEs to deliver solutions into production to benefit customers or an area of the business.
- You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects.
- You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs.
- You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly
- You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics.
- You invent, refine and develop your solutions to ensure they are meeting customer needs and team goals. You keep current with research trends in your area of expertise and scrutinize your results.
- Experience in mentoring junior scientists
A day in the life
You will be working with a group of talented scientists on researching algorithm and running experiments to test solutions to improve our experience. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, model development and productionizing the same. You will mentor other scientists, review and guide their work, help develop roadmaps for the team.
We are open to hiring candidates to work out of one of the following locations:
Banagalore, KA, IND | Bangalore, IND | Bangalore, KA, IND
BASIC QUALIFICATIONS
- 5+ years of building machine learning models for business application experience
PREFERRED QUALIFICATIONS
- 4+ years of applied research experience
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
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