Senior Applied Scientist, Amazon Core Search

Amazon is hiring a Senior Applied Scientist, Amazon Core Search in Bengaluru, India. Level rates it ; you can apply on Amazon.

Level's read on this job

Builds AI ●●●● is how Level rates this applied scientist role: the job is building AI systems.
Tools and skills the posting cites include TensorFlow, scikit-learn and Python.
Level classifies it as a senior role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Leads machine learning and NLP initiatives to develop scalable semantic search and autocomplete models for Amazon Core Search.

TensorFlowscikit-learnPythonPyTorch

nlpmachine-learningdeep-learningreinforcement-learninginformation-retrieval

We are embarking on a multi-year journey to improve the shopping experience for customers globally. Amazon Search team creates customer-focused search solutions and technologies that make shopping delightful and effortless for our customers. Our goal is to understand what customers are looking for in whatever language happens to be their choice at the moment and help them find what they need in Amazon's vast catalog of billions of products — starting from the very first keystroke.

As Amazon expands to new interfaces, we are faced with the unique challenge of maintaining the bar on Search Assistance and Search Quality.

We are looking for a Senior Applied Scientist to work on improving search on Amazon using NLP, ML, and DL technology. As an Applied Scientist, you will lead our efforts in search autocomplete — developing high-quality suggestions. You will build systems that anticipate search query intent and surface the right suggestions and results. As part of this role, you will develop high precision, high recall, and low latency solutions for search. Your solutions should work for all languages that Amazon supports and will be used in all Amazon locales world-wide. You will develop scalable science and engineering solutions that work successfully in production. You will work with leaders to develop a strategic vision and long term plans to improve search globally.

We are growing our collaborative group of engineers and applied scientists by expanding into new areas.

Key job responsibilities
As an Applied Scientist on the team, you will lead science innovation to improve the customer search experience through higher-quality autocomplete search results. You will:

- Develop and deploy ML models to produce high-quality, diverse search autocomplete suggestions.

- Design and train semantic matching models (bi-encoders, cross-encoders, and distillation from large foundation models) for suggestion ranking and relevance.

- Develop reinforcement learning and reward-modeling approaches to continuously improve suggestion quality.

- Train multi-objective ranking and scoring systems that balance suggestion diversity, specificity, and relevance.

- Design and implement scalable model architectures optimized for strict latency constraints, including knowledge distillation, quantization, and efficient inference strategies for production deployment.

- Lead end-to-end science projects from problem formulation through production launch, mentoring scientists and collaborating closely with engineers and scientists within and outside the team to deliver customer-facing impact.

Basic qualifications

- PhD, or Master's degree
- 6+ years of building machine learning models or developing algorithms for business application experience
- 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.

How we rate this

Senior Applied Scientist, Amazon Core Search at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Applied Scientist, Amazon Core Search is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in IN, KA, Bengaluru.
The job was posted on July 18, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

NLPMachine learningDeep learningReinforcement learningInformation RetrievalTensorFlowscikit-learnPython

Also common in applied scientist jobs at this level

LLM Generative AI AWS Computer vision PyTorch Fine-tuning

Pay

Typical applied scientist job: $167k

This posting doesn't list pay. Use the typical applied scientist figure when pay comes up. See applied scientist jobs

Questions you could be asked

What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where deep learning was part of your work. What did you do?
Tell me about a project where reinforcement learning was part of your work. What did you do?
Tell me about a project where information retrieval was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: NLP, Machine learning, Deep learning, Reinforcement learning, and Information Retrieval. 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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