Intern in Machine Learning – Image Processing
Lausanne, Switzerland
vor 2 Tg.

Over the past three years, Philip Morris International (PMI) has made a dramatic pivot away from the marketing and sales of combustible cigarettes, and moved towards its Reduced-

Risk Product (RRP) portfolio, focusing on its flagship product, IQOS.

This launch of this product is PMI’s step forward to creating a smoke-free future for legal age consumers who continue to enjoy tobacco, but are seeking smoke-free alternatives.

All of this has been accompanied by an organization-wide transformation in ways of working, culture, and strategy, with emphasis on digital, consumer and collaborator strategies.

Do you look for ways to learn and grow in an international environment?

Do you want to build a remarkable career?

Are you up for a 6-month challenge starting as of July / August 2019?

Then apply now, we need you :

You have the following skills and qualifications :

  • Currently studying for your Master degree in Computer science or related area
  • Familiarity with ML frameworks for object detection (YOLO, PyTorch, Keras, Tensorflow, etc.)
  • Solid programming skills in Python, Knowledge of Scrum, TDD
  • Unix shell scripting
  • Gitflow workflow
  • A desire to learn and strong motivation to succeed Responsibilities :
  • Use ML techniques to analyze stream of images to detect specific objects in them
  • Identify the most effective object detection techniques
  • Develop an approach to address labelled data bottleneck
  • Assess the quality of the devised analytical solution Project Description :
  • We are looking for a Machine Learning Intern to join PMI Data Science Team.

    In this project we aim to investigate various deep learning architectures, pre-trained models and API's to extract insights from visual data.

    For example, given a stream of pictures, a suite of purpose-built models can extract various types of contextual information using object detection and segmentation models, e.g. :

    person’, male’, female’, group’, garden’, bar’, beach’, drink’, color spectrum’, brands’, etc.Objective is to leverage on the existing models & data pipelines and explore the visual aspect of the image data.

    Extracted data related to visual entities will be made available for other data scientists & business users for further exploration.

    References :

  • Mask R-CNN for object detection and segmentation
  • A great starting point for all sorts of pre-trained models and papers Philip Morris International :
  • Building a Smoke-Free Future Philip Morris International (PMI) is leading a transformation in the tobacco industry to create a smoke-

    free future and ultimately replace cigarettes with smoke-free products to the benefit of adults who would otherwise continue to smoke, society, the company and its shareholders.

    PMI is a leading international tobacco company engaged in the manufacture and sale of cigarettes, smoke-free products and associated electronic devices and accessories, and other nicotine-

    containing products in markets outside the U.S.

    PMI is building a future on a new category of smoke-free products that, while not risk-free, are a much better choice than continuing to smoke.

    Through multidisciplinary capabilities in product development, state-of-the-art facilities and scientific substantiation, PMI aims to ensure that its smoke-

    free products meet adult consumer preferences and rigorous regulatory requirements.

    PMI's smoke-free IQOS product portfolio includes heated tobacco and nicotine-containing vapor products.

    As of Dec.

    31, 2018, PMI estimates that approximately 6.6 million adult smokers around the world have already stopped smoking and switched to PMI’s heated tobacco product, which is currently available for sale in 44 markets in key cities or nationwide under the IQOS brand.

    For more information, see our PMI and PMIScience websites.

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