Join the company’s growing team and take part in our expansion in Switzerland and internationally.
As a Junior Machine Learning Engineer, you will be working on a variety of applied research projects using state-of-the-art Machine learning techniques and you will help deploy them for customers, transforming their business.
You will contribute to an exciting environment with a challenging team always on the lookout to learn and share about the latest technologies and applications.
What we offer:
- A workplace with numerous exciting and challenging projects applying state-of-the-art Artificial Intelligence in diverse industries for the world’s best brands
- A position that enables you to have an impact on 1’000s of people
- A position that has you challenged daily and enables you to have a steep learning curve
- A welcoming team with a fun and dynamic spirit
- A workplace with a startup culture and that fills your work with purpose
- Offices on a brand new campus in Lausanne and at the Technopark in Zurich
- Cross offices/company-wide frequent team events
- Student, you have an internship to complete as part of your studies
- Data enthusiast, you are not scared to dive in and to ask the right questions
- Resourceful & critical thinking
- Collaborative and team-oriented spirit
- Impeccable attention to details and drive to excel
- Fast learner and have a problem-solving attitude, the projects you will work on are not textbook cases, you will need to be imaginative to bring the best solutions
- With strong communication skills, you will most likely have to present your results to non-technical people
- You have a growth mindset, always on the lookout on what you can improve, rationalize and consolidate
- You are willing to always go the extra mile and never compromise on quality
- Proactive attitude, not hesitating to act and take on responsibilities
- Organizational skills and capacity to adapt in an ever-evolving startup environment
In addition, this should be part of your background to apply
- Proficiency in Python programming
- Experience with ML/DL libraries and frameworks (es. Scikit-learn, TensorFlow, Keras, Pytorch)
- Experience with various visualization frameworks (es. Matplotlib, Seaborn, Bokeh, Power BI, Tableau, D3.js, etc.)
- Experience in applying deep learning approaches, such as recurrent neural networks and deep convolution networks
- Strong knowledge of clustering algorithms, regression and classification (supervised/unsupervised/reinforcement learning)
- Understanding of Unix/Linux operating systems
- Familiarity with web development is a plus
- Familiarity with REST API and microservices
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