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Machine Learning Engineer

Drive our machine learning pipelines and data science projects forward. Our focus spans from research to production, including graph neural networks, motif discovery, conformal prediction, Topological Data Analysis, and a variety of anomaly detection methods for industrial time-series analytics. A comfortable proficiency in PyTorch and common libraries for time-series analytics is vital.


Sarnen / Aachen


Working Student or Internship

What You’ll Do

    Alpamayo, a tech startup and CSEM spinoff, is focused on creating intelligent maintenance and quality solutions for industrial applications. Our goal is to make these solutions more accessible through the development of PREKIT, a framework for process monitoring and predictive analytics. Combining in-depth process expertise with the power of AI, we strive to meet the intricate needs of machine manufacturers.

    PREKIT, our suite of software modules, is designed to encapsulate this approach. It empowers engineering teams to leverage their expert problem understanding to design powerful analytics solutions. The suite assists equipment manufacturers in providing valuable digital services to connected machines globally. Deployable as an end-to-end solution, PREKIT aids users right from initial pilot implementation to running a scalable, fully-managed service. Alternatively, it can seamlessly integrate with customers' existing digital ecosystems.
    As we grow, we're searching for driven student workers eager to join our technical team.

    You will recieve guidance from our CTO in developing cutting-edge knowledge-infused AI algorithms:

    - Create, implement, and automate data ingestion, data selection, and data processing jobs in our backend architecture.

    - Translate best practices from data-driven predictive maintenance projects into robust AutoML capabilities .

    - Orchestrate model (re-)training jobs and automated model monitoring to create an optimized MLOps system.

Who You are

    - Educational Background: Pursuing a degree Computer Science, or related field.

    - AI & Machine Learning: Familiarity with AI methodologies and the development of machine learning algorithms.

    - Adaptability: Comfortable in fast-paced environments with the aptitude to learn quickly and pivot tasks when required.

    - Initiative: Willingness to take ownership of tasks, from conception to deployment, and drive projects forward.
    - Proficiency in Python and experience with relevant tools for data analytics, such as Pandas, PyTorch, and SkLearn.

    Experiences with these languages/tools are helpful, but you can also learn them as you go:
    - Apache Airflow
    - .NET
    - PostgreSQL
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