Company
Tomra logo

Tomra

www.tomra.com
Location

Hybrid work from Mülheim-Kärlich:

  • 🇩🇪 Germany
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Python Software Developer - Deep Learning Tooling *

Company Description

  • FULL TIME

  • Mülheim-Kärlich, Germany

Who are we?

Today, we are not utilizing resources in a sustainable way. In fact, the world is only 9% circular, meaning much of the Earth’s precious resources are only used once, leaving huge untapped potential for more sustainable resource management. TOMRA provides cutting-edge solutions for optimal resource productivity within the recycling, mining and food industries and is therefore uniquely positioned to shape the Circular Economy, creating demand for this way of thinking in the world. At TOMRA we want to be a thought leader, encouraging a more sustainable way of thinking and inspiring active change around the world.

Job Description

As a Python Software Developer specializing in Deep Learning Tooling, your primary role will be to design and implement software tools that facilitate the creation of image-based Deep Learning models which are created to run on our sorting machinery.

Your expertise will empower colleagues without a computer science background to seamlessly organize and interact with large volumes of sensor data, thereby facilitating the creation of Deep Learning models. This will also include the enhancement of our existing training and evaluation pipeline.

You will contribute to the development of production-ready Deep Learning components integrated into our machines, while fostering a strong cooperation within an interdisciplinary R&D team.

Key Responsibilities:

  • Creation of software tools and services to encapsulate Deep Learning approaches to allow non-computer scientist to organize and work with huge amounts of sensor data with the goal to create Deep Learning models.

  • Integrate Deep Learning algorithms for real-time data analysis, especially convolutional neuronal networks

  • Develop, optimize and verify

    • Training and evaluation pipelines,

    • Tools for data acquisition and classifier training,

    • Interfaces to machine software for real-time analyse and classification.

  • Provide internal support post-rollout of the developed tools and services.

  • Propose enhancements for tool quality and efficiency.

  • Generate comprehensive technical documentation.

Qualifications

  • Bachelor’s degree in computer science or similar qualification

  • Proven experience in software engineering.

  • Proficiency in Python.

  • Familiarity with C++ and CUDA is preferred.

  • Familiarity with machine learning, particularly deep learning, is beneficial.

  • Experience with one or more deep learning frameworks is desirable.

  • Understanding of image processing algorithms is an added advantage.

  • Strong verbal and written English skills.

  • At least basic knowledge of German.

Additional Information

Your benefits

  • 30 days annual leave;

  • Supported company pension scheme;

  • Supported group accident insurance;

  • International SOS for private use;

  • Hybrid working principles, flexible working hours;

  • Opportunity to purchase TOMRA shares;

  • Employee benefit discounts for TOMRA Online Shop;

  • Company (e-) bike leasing;

  • Gym membership coverage support;

  • Office comfort: free parking spaces, canteen, coffee machines;

  • Professional and personal development: learning on the job, specialized course, conferences etc.;

  • Coaching opportunities - Individual Development Programs;

  • Norwegian corporate culture (no hierarchical thinking, transparent communication culture).

Are you interested?

Please send your...

  • CV (in English);

  • Motivation letter in English (in short: why you are a good fit for this position);

 

* Tomra does not differentiate on the basis of gender, race or ethnicity, religion, color, sexual orientation or identity, disability, age, or other protected statuses as given by applicable law. We are committed to creating a diverse and inclusive environment and are proud to be an equal opportunity employer.

Most importantly, it’s a match!

 

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