Junior/ Senior Machine Learning Engineer (all genders)

Würzburg / Germany

The future belongs to companies, who are successfull while also having a clear conscience and being aware of their responsibility. We assist businesses and organizations making the necessary changes with innovative and data-driven solutions.

The people, who work at Ingdilligenz, want to combine their professional success and personal advancement with a fun, interesting and purposeful work environment. We think that a good salary should be accompanied by the pleasant feeling of being able to impact something and making the world a tiny bit better.

Currently we are looking for a

Junior/Senior Machine Learning Engineer (all genders)

to develope sustainability solutions based on Data & Analytics.

Your tasks

• designing & implementing Data Science & AI applications/solutions for us or our clients
• evaluating state-of-the-art AI frameworks and their potential scope of application
• developing, automating & deploying AI models to support sustainability analysis
• feasibility analysis of problems regarding realization using Artificial Intelligence

Your profil

• a university degree (ideally in computer science, information systems, mathematics, science or computer linguistics)
• excellent programming skills in Python and/or R
• programming experience (e.g. Java, C++ or C#)
• theoretical knowledge as well as hands-on experience in the areas of Machine Learning and Artificial Intelligence
• ideally sufficient knowledge in SQL, Data Science and cloud platforms

What is important to us

• Dedication and personal interest in the developments regarding sustainability in the corporate world
• Flexibility, willingness to learn and high quality standards
• Honesty, respect and transparency
• Organizing joint activities (frequent meetings, teambuilding events, social and environmental activities)
• Our actions being climate neutral

What we offer you

• A young, motivated team with exciting projects in multiple different sectors
• Room for developing your own ideas and approaches to enhance sustainability
• A wide variety of tasks, tools and methods to design and shape the future
• Attractive conditions (social package, flexible work hours, ability to mainly work remotely, development opportunities tailored to your personal strengths and preferences