Junior Machine Learning Scientist - Berlin, Deutschland - Kineo GmbH

Kineo GmbH

Geprüftes Unternehmen

Berlin, Deutschland

vor 5 Tagen

Geschrieben von:

Lena Wagner

beBee Recruiter

Beschreibung

We are Kineo, a Berlin-based tech startup developing machine learning solutions that bring real, tangible business value to our clients.

Through our expertise, mindset, culture and most importantly with your help we are turning the AI landscape upside down. Are you up for the challenge?

Our proposition to you

We vouch to create a space where you can explore different sets of complex problems and data across industries and verticals.
To support you in your personal development, everyone at Kineo has a mentor. When you grow, so does Kineo.
Your decisions matter You will not have a boss who decides things for you. At Kineo we believe that decisions are best made locally, by the people closest to the problem at hand.
Transparent salary and career planning from day one.
A beautiful office in the centre of Kreuzberg, with tons of benefits, such as free drinks, snacks, consoles etc.
Flexible, familyfriendly work environment we have parents in the team and support them.

Success in the role means that you will have

After 2 months: You established yourself as a member of the team and have already contributed to one of our client projects. You have a clear understanding of how we work and can independently navigate our technical architecture.
After 6 months: You are a key member of the team and fully involved in the development of a client project. You will have made notable contributions to our codebase and internal processes.

Your Character Traits

Strong inner drive to get things done: you're not waiting for others to manage or tell you what to do. You are selfdriven and you like to work autonomously.
You hate boxes: You don't stop when your thing is done, and you don't point to the other side. Instead, you are eager to learn and support in areas that may not be your core expertise.
Quality ambassador: you combine an obsession with quality with a highly pragmatic prioritisation of tasks to maximize your project throughput.
Exceptional communicator: you have excellent communication, presentation and interpersonal skills that enable you to quickly establish an emotional bond.

You fit in with our team culture if you

Enjoy working in an environment that combines pragmatic, commercial thinking with a strong desire to learn and grow together. We value team players, not data ninjas.
Have a highly ambitious, curious and driven mindset while being able to convey humility and respect for different opinions.
Feel like a global citizen with a strong passion for openness and diversity.
See open feedback, accountability and independent thinking as the foundation for exceptional (team) work.

Tasks

You will work as part of smaller teams of 23 people on developing machine learning solutions with our clients.
You will conceptualize and implement algorithmic solutions to challenging business problems. This includes prototyping and productionizing of machine learning solutions, and also defining and analysing product use cases together with the customer.
You will own machine learning solutions from the first drop of raw data, all the way into production serving millions of inference requests.

Requirements:

An advanced quantitative degree e.g Mathematics, Statistics, Computer Science or related fields. Strong knowledge of theoretical math and CS.
Knowledge of working with large structured and unstructured data sets. Knowledge of data engineering tools like Apache Spark is an advantage.
Strong programming skills in Python. We love other languages too, but Python is what we (and you) will use.
Experience in using a wide range of ML frameworks such as SKLearn, Tensorflow, Torch in production. Experience with domain specific libraries like OpenCV, HuggingFace etc are an advantage.
Excellent written and verbal communication, with the ability to work crossfunctionally with nonscientific experts.

Last but not least, keep in mind that we are hiring value based, not skill based.

That being said, please tell us the following in your contact message: