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Amazon·E-commerce·1 day ago
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Applied Scientist, International Machine Learning

Delhi NCR, IndiaFull-timeOn-siteMid · 2-5 yearsMachine Learning Engineer

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Must-have skills for this role

  • machine learning
  • java
  • c++
  • python

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What you'll do

  • Use machine learning and analytical techniques to create scalable solutions for business problems
  • Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes
  • Design, develop, evaluate and deploy, innovative and highly scalable ML models
  • Work closely with software engineering teams to drive real-time model implementations
  • Work closely with business partners to identify problems and propose machine learning solutions
  • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance
  • Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production
  • Leading projects and mentoring other scientists, engineers in the use of ML techniques

What they're looking for

  • Experience programming in Java, C++, Python or related language
  • Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

Nice to have

  • Experience implementing algorithms using both toolkits and self-developed code
  • Have publications at top-tier peer-reviewed conferences or journals

Summarised by NextRaise from the employer’s description, which follows in full below.

Full description from employer

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced ML systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real-world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for International Emerging Stores (IES).

Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions

We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the International Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML.

Key job responsibilities
Use machine learning and analytical techniques to create scalable solutions for business problems
Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes
Design, develop, evaluate and deploy, innovative and highly scalable ML models
Work closely with software engineering teams to drive real-time model implementations
Work closely with business partners to identify problems and propose machine learning solutions
Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance
Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production
Leading projects and mentoring other scientists, engineers in the use of ML techniques


About the team
International Machine Learning Team is responsible for building novel ML solutions across International Emerging Store (India, MENA, Far-East, LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide

Basic Qualifications

- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

Preferred Qualifications

- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals

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.
E-commerce

Company

AmazonE-commerce
Delhi NCR, India

Company facts come from this company's own listings. We only show what the postings themselves carry.

Sourced from Amazon's careers site·first seen 22 Sept 2026·last verified 22 Sept 2026·How we source jobs

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