Applied Scientist, GTTS Science

Amazon

Luxembourg, LUX

il y a 4j

Job summary

Are you interested in building state-of-the-art machine learning and optimization systems for the most complex, and fastest growing, transportation network in the world?

If so, Amazon has the most exciting, and never-before-seen, challenges at this scale (including those in sustainability, e.g. how to reach net zero).

Amazon’s Global Transportation Tech Services (GTTS) builds technology to manage the most complex transportation network on earth.

Our software enables thousands of operators worldwide to build and run the fastest and most reliable transportation network.

We use the cutting edge technologies provided by AWS, operation research and machine learning practices to scale, transportation operations through digitization and automation of complex business process.

As part of this team you will focus on the development and research of machine learning solutions and algorithms for core planning / simulation systems and applications within GTTS and impact the future of the Amazon delivery network.

Current research and areas of work within our team include machine learning forecast, NLP, model interpretability, Combinatorial / Continuos optimization problems, among others.

Key job responsibilities

Responsibilities :

Build Machine Learning models from A to Z, from problem definition to deployment.

Validate models via statistically rigorous A / B experiments

Work closely with other scientists to test, prototypes, and integrate successful models and algorithms in production systems at very large scale;

Lead science work, mentor junior scientists and work side by side with fellow applied scientists in the team.

BASIC QUALIFICATIONS

PhD in Computer Science, AI, Mathematics, or Statistics with specialization in ML (alternatively, MSc. and 3+ years in a ML scientist role).

Deep knowledge of fundamentals, and the state-of-the art, in relevant areas of ML.

Fundamentals in problem solving, computer science, algorithm design, complexity analysis, mathematics and statistics

Proficiency in at least one major programming language (Java, C++, Python, Scala or similar). The more the merrier.

Strong verbal and written communication skills.

PREFERRED QUALIFICATIONS

3+ years of experience, and strong expertise, in any of : Machine Learning, time series forecasting, NLP, Graph neural network, Combinatorial / Continuos optimization problems.

Experience with cloud computing services such as AWS.

Experience working effectively with research science, data engineering, and software engineering teams.

Proven track record of innovation in creating novel algorithms and applying the state-of the-art.

Track record of publication in Tier 1 ML conferences.

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