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Deep Learning Engineer - Visual Data Science

Älmhult, Kronoberg IT & Digital Solutions Full Time

Job description

Company description

Deep Learning Engineer – Visual data science - IKEA Communications AB

What if you could inspire to make everyday life just a little bit better?  

The answer is simple: You can. This is what motivates us at IKEA. We’re constantly searching to find new ways to be better. We use insights from real life at home all over the world, learning about the needs and dreams of people. We use our home furnishing knowledge to help inspire people with ideas and solutions that will help them live the life they want.  

At IKEA Communications, we’re people-centric, have a passion for making great stuff, and we aim to be the best communication partner for the whole of IKEA. We work closely and together with our colleagues across IKEA, creating state-of-the-art communication at the lowest price. Located in Älmhult, Sweden, we’re a melting pot of many different nationalities and cultures. Because in order to make things better for the many, we want to involve people from all parts of the world. Nonetheless, we never forget our Swedish heritage that forms the backbone of who we are today.  

We’re on the lookout for passionate doers, idea makers, creative thinkers - people who want to find answers to everyday problems in people’s lives, for society and the planet. Do you also believe in celebrating the everyday life?  

Do you want to be part of making it happen from idea to paper or pixel? Then keep on reading. 


Job description

The Digital Area is set up to connect, enable and support all IKEA Communications Areas with IT systems and tools to create, produce and deliver communication in the smartest, most automated and cost-efficient way possible.    

The Digital Lab is part of the Digital Area and drives the digital development and innovation work in the spatial computing area for all IKEA companies. The Digital Lab is right now looking for a Deep Learning Engineer.  

As a Deep Learning Engineer in the IKEA Digital Lab, you will create, develop and transfer knowledge related to deep learning within the field of spatial computing and visual machine learning. You will act as a connection between IKEA needs and possible technical solutions available or being developed on the market in technical research & development environments. 

Essential parts of the assignment will be to:  

  • Implement, maintain, and evaluate deep learning and visual machine learning architectures on a variety of platforms including mobile platforms, workstations, and high-performance compute resources. 
  • Take part in the creation “proof-of-concept” applications based on deep learning algorithms within the field of spatial computing and visual machine learning; including exploration, optimization and simulation techniques. 
  • Develop and implement data structures and pipelines for systematic evaluation and systematic comparison of different machine learning solutions 
  • Develop, implement and maintain tools for data annotation for large image data sets for training and evaluation of machine learning solutions 
  • Work with systematic evaluation to improve deep learning and/or general artificial intelligence models/systems as well as the training/testing data used. 

Qualification

The Deep Learning Engineer we look for is someone that have a passion to learn new things and a have a hands-on attitude. Someone with deep Interest for the future of deep learning/machine learning. Someone who is highly motivated to work in teams and collaborate within new constellations, both internal and external teams. Someone who contribute to an innovative and creative with positive attitude, problem solving and lateral thinking. 

You´ll need: 

  • BSc or MSc, or equivalent advanced degree/academic background in Computer Science or other similar field with documented course components in Machine & Deep Learning and computer vision/graphics. 
  • 3-5 years’ experience from working with implementation and maintenance of machine learning/deep learning. 
  • Experience in working with cloud computing platforms (Azure, AWS, or similar). 
  • Experience working (installation, maintenance and usage) with popular deep learning toolkits (TensorFlow, MXNet, PyTorch, Caffe etc) 
  • Experienced in administrating operating systems including different Linux flavours e.g. Ubuntu or Fedora. 
  • Experience in computing on different platforms from mobile to GPUs and high-performance computing.  
  • Experienced in appropriate programming languages (Python, C/C++) 
  • Fluent in English (written and spoken) 

We are looking for two Deep Learning specialist with different previous experience. Take a look at the other advert on the link bellow to assess which one is the best fit for you: 

https://smrtr.io/3QS3W


More Information

This is a place where you can focus on doing what you love. There are no dress codes or closed offices. No day is ever the same. All ideas are welcome. Everyone tries to pitch in when needed, and failures are seen as a way of learning. When you enter our building, we want you to feel that you can inspire billions of people all over the world. Are you ready to make the world a little better, together? We want to hear from you!  

We look forward to receiving your application in English and link to previous work as soon as you have decided that this could be something for you.  

This position was posted 2019-02-03 and may be online for up to 3 weeks following this date. We do not have an application deadline for this position. We take candidates into the recruitment process continuously and close the position down once we have found the right candidate.  

We do not accept applications by e-mail. If you are one of the candidates, we think have the required experience we will contact you by email or phone to plan a telephone interview. In some cases, recruitment processes may take time, so we kindly ask you to be patient in this regard. 

If you have any questions regarding this position or recruitment process, please contact Recruiter, +46 72 886 53 84