Data Scientist with AI Edge Expertise

1 day ago


Stockholm, Stockholm, Sweden Ninox Limited Full time

We are seeking a highly skilled Senior Machine Learning Engineer / Data Scientist to join our team in Stockholm. If you have excellent programming skills and enjoy working on the forefront of artificial intelligence, this role may be suitable for you.

About Ninox Limited

Ninox Limited is a scale-up driving innovation at the edge of artificial intelligence and tiny machine learning. Our company enables the development of intelligent products through our SaaS solution, Imagimob AI. We work closely with customers and partners from Europe, North America, and Asia-Pacific.

Our team consists of almost 20 employees, divided into three teams: Sales & Marketing, Product Development, and Customer Success. In May 2023, Infineon Technologies AG acquired 100% of the shares in Imagimob, and we now belong to the Connected Secure Systems division.

About the Position

In this role, you will become a key member of our cross-functional teams, collaborating with innovative AI engineers to develop next-generation AI-powered products. As a member of our Customer Success team, you will work closely with customers, taking an active role in everything from AI modeling, programming, data collection to system testing and verification.

Your creativity will be challenged daily as you tackle diverse customer challenges and issues. You will also participate in strategic planning, contribute to shaping our product offerings, and drive initiatives that align with our long-term vision.

Responsibilities

  1. Provide rapid solutions to customers using our products and services.
  2. Tackle a diverse range of customer challenges and issues.
  3. Participate in strategic planning and contribute to shaping our product offerings.
  4. Develop and deploy efficient AI/ML solutions for edge applications.
  5. Collaborate with the product team to create customer-specific solutions.
  6. Work with the sales team to promote products and projects.
  7. Contribute to the development of infrastructure supporting model deployment and efficiency.


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