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Applied Scientist II, Last Mile Address Intelligence (LMAI)

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Amazon

15d ago

  • Job
    Full-time
    Mid Level
  • Science
    Data
  • Bangalore, +1

AI generated summary

  • You need 3+ years in model building, publications or patents, programming in Java/C++/Python, experience in algorithms, Unix/Linux, and professional software development, plus a Master’s degree.
  • You will tackle complex business problems, customize GenAI models, manage end-to-end project workflows, and explore open-ended ML directions for potential publication in conferences.

Requirements

  • 3+ years of building models for business application experience
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience programming in Java, C++, Python or related language
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
  • Experience using Unix/Linux
  • Experience in professional software development
  • Master's degree

Responsibilities

  • Key job responsibilities
  • As an Applied Scientist II, your responsibility will be to deliver on a well defined but complex business problem
  • Explore SOTA technologies including GenAI and customize the large models as suitable for the application
  • Work on a end-to-end business problem from design to experimentation and implementation
  • There is also an opportunity to work on open ended ML directions within the space and publish the work in prestigious ML conferences

FAQs

What qualifications are required for the Applied Scientist II position in Last Mile Address Intelligence?

The position requires 3+ years of experience in building models for business applications, experience with patents or publications in top-tier peer-reviewed conferences or journals, and programming skills in Java, C++, Python, or related languages.

What areas of expertise are needed for this role?

Candidates should have knowledge in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, and high-performance computing.

What are some key responsibilities of this position?

As an Applied Scientist II, you will be responsible for delivering on complex business problems, exploring state-of-the-art technologies including GenAI, and working on end-to-end business problems from design to experimentation and implementation.

What kind of problems will I be working on in this role?

You will work on problems related to address normalization, geocode learning, maps learning, and time estimations for delivery predictions, among others.

Is there an opportunity for publishing research in this role?

Yes, there is an opportunity to innovate, explore state-of-the-art techniques, and publish research in internal and external ML conferences.

What kind of technologies will I be using?

You will be using technologies such as LLMs, weak supervision, graph-based clustering, entity matching, computer vision, optimization techniques, and supervised learning methods.

What is the structure of the team?

The Last Mile Address Intelligence (LMAI) team is led by Saurabh Sohoney and operates across HYD13 and BLR26 locations, with support from the Geospatial science team led by Amber Roy Chowdhury.

Do I need to have a specific degree for this position?

A Master's degree is preferred for this position.

Is experience with Unix/Linux required?

Yes, experience using Unix/Linux is a required qualification for this role.

What experience in software development is expected?

Candidates should have experience in professional software development as part of their qualifications for this position.

Retail & Consumer Goods
Industry
10,001+
Employees
1994
Founded Year

Mission & Purpose

Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. We are driven by the excitement of building technologies, inventing products, and providing services that change lives. We embrace new ways of doing things, make decisions quickly, and are not afraid to fail. We have the scope and capabilities of a large company, and the spirit and heart of a small one. Together, Amazonians research and develop new technologies from Amazon Web Services to Alexa on behalf of our customers: shoppers, sellers, content creators, and developers around the world. Our mission is to be Earth's most customer-centric company. Our actions, goals, projects, programs, and inventions begin and end with the customer top of mind. You'll also hear us say that at Amazon, it's always "Day 1."​ What do we mean? That our approach remains the same as it was on Amazon's very first day - to make smart, fast decisions, stay nimble, invent, and focus on delighting our customers.