Artificial Intelligence and Machine Learning Working Student (m/w/d)

  • NetApp
  • Berlin, Germany
  • 13/07/2022
Full time Machine Learning Artificial Intelligence Software Engineering DevOps

Job Description

Job Description

employment type
full time

Full job description

Job Summary
We are looking for an intern/working student to work within an expert team of Artificial Intelligence, Machine Learning and Deep Learning specialists. You will support this team on building architectures and developing AI, ML and DL related solutions to deliver world class practices within data engineering and machine learning modelling.
This means in more detail:
Building production ready AI solutions on-prem and cloud
Automate ML model training and production ready deployment
Setup CI/CD pipelines for AI solutions (MLOps and DataOps)
Managing AI Workflow at Scale
Desired Attributes
Experience with AI, ML, DL and Analytic engagements
Understanding of machine learning, DNNs, CNNs, RNNs, federated learning, supervised and unsupervised learning, and optimization techniques
Good to have experience in predictive analytics, data mining and processing data at scale, based on structured and unstructured data
experience in working with some of the following programming languages ​​and frameworks: Python, R, Julia, Tensoflow, PyTorch, Kubeflow, KFServe, Hadoop, Spark or comparable products.
Optional Attributes
Exposure to GPU, Container and Kubernetes
Experience with database systems including BigQuery, Postgres, etc.
Knowledge and experience in some of the key AI platform, eg Microsoft Azure, Google AI, Amazon AWS
Education
You must be a current student in a Bachelor / Master degree in one of the following technical disciplines: Computer Science, Software Engineering, Information Technology or related subjects like Mathematics, Physics.
You should have the unrestricted right to work in Germany for the entire duration of the internship / working student contract.
You are available to work between 6 to 12 months either part time or full time (depending on course requirements).
Happy to work in a virtual environment while social distancing restrictions or office closures are in place. We take the health and safety of our employees seriously.