AmazonPosted 4w ago

Senior Applied Scientist, Search Relevance International

Senior Applied Scientist, Search Relevance International at Amazon scores 86 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

IN, KA, Bengaluruseniorfull-time

AI in this role

tensorflowscikit-learn

The Amazon Search team creates customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Our Search Relevance team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide.

Amazon has grown rapidly and will continue to do so in foreseeable future. Providing a high quality search experience is a unique challenge as Amazon expands to new customers, countries, categories, and product lines. We are seeking a strong applied scientists to join the newly formed Relevance India team. This team’s charter is to increase the pace at which Amazon expands and improve the search experience at launch. In practice, we aim to invent universally applicable signals and algorithms for training machine-learned ranking models and improve the machine-learning framework for training and offline evaluation that is used for all new relevance models.

Key job responsibilities
Build machine learning models for Product Search.
Develop new ranking features and techniques building upon the latest results from the academic research community.
Propose and validate hypothesis to direct our business and product road map. Work with engineers to make low latency model predictions and scale the throughput of the system.
Focus on identifying and solving customer problems with simple and elegant solutions.
Design, develop, and implement production level code that serves billions of search requests. Own the full development cycle: design, development, impact assessment, A/B testing (including interpretation of results) and production deployment.
Collaborate with other engineers and related teams within A9.com and Amazon.com to find technical solutions to complex design problems.
Take ownership. Understand the needs of various search teams, distil those into coherent projects, and implement them with an eye on long-term impact.
Be a leader. Use your expertise to set a high bar for the team, mentor team members, set the tone for how to take on and deliver on large impossible-sounding projects.
Be ambitious. Find and eagerly tackle hard problems.
Be curious. You will work alongside systems engineers, machine learning scientists, and data analysts. Your effectiveness and impact will depend on discussing problems with and learning from them. You will have access to the technologies and vast technical tools and resources of Amazon and will need to learn how to use them effectively.
Be customer focused. Work backwards from customer problems, figure out elegant solutions, and implement them for speed and scalability.

Basic qualifications

- 6+ years of building machine learning models for business application experience
- PhD, or Master's degree
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

Preferred qualifications

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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Skills and AI tools this role asks for

TensorFlowscikit-learn

Questions you could be asked

What's a project where you used TensorFlow hands-on?
Walk me through how you've used scikit-learn in your day-to-day work.
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

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List these exact terms on your resume: TensorFlow and scikit-learn. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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