Logo Qimia

Data Engineer/Data Scientist

Qimia

Job

  • Level
    Experienced
  • Job Field
    Data
  • Employment Type
    Full Time
  • Contract Type
    Permanent employment
  • Location
    Cologne
  • Working Model
    Onsite

    • Job Summary

    In this role, you will develop innovative AI and Machine Learning solutions, particularly Generative Deep Learning models, and implement data-driven systems using Python tools in a cloud environment.

    Job Technologies

    Your role in the team

    • Development of innovative AI and Machine Learning solutions.
    • Development of Generative Deep Learning Models: Creating, training, and fine-tuning neural networks with Python tools such as Torch, Numpy, Pandas, PySpark, Jupyter, Transformers, Datasets, Tiktoken, and Wandb.
    • Natural Language Processing (NLP) using libraries from the HuggingFace ecosystem (Python-based deep learning library for LLMs) - Transformers, Datasets, Tokenizers, and Accelerate - as well as pre-trained Hugging Face Hub models.
    • Design and development of ML systems for production-ready applications that are reliable, scalable, maintainable, and adaptable to changing business requirements.
    • Development of MLOps pipelines for automation, continuous development, evaluation, and deployment of models.
    • Development of monitoring systems for the rapid detection and resolution of issues that models may encounter in production.
    • End-to-End design and implementation of data analytics systems; this includes data collection, requirements engineering and specification, as well as the design of technical solutions based on business requirements.
    • Identification and recognition of opportunities for designing and implementing Internet-Scale Data Mining solutions in close collaboration with other Data Scientists and Data Engineers.
    • Development of ETL pipelines for large and complex datasets; processing of structured and unstructured data with Spark, Pandas, Dask, Kafka, etc.
    • Prototyping and implementation of massively scaled data analytics solutions based on big data tools (Spark, DWH, SQL, Python, and R).
    • Working with cloud platforms (AWS, Azure, and Google Cloud).

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    Our expectations of you

    Education

    • Master's degree in Computer Science or similar quantitative programs such as Statistics, Operations Research, Bioinformatics, Mathematics, or Physics.

    Qualifications

    • Fluent in German and/or English.
    • Master's degree in Computer Science, Machine Learning, or similar technical fields. (preferred)

    Experience

    • 1 year of professional or academic experience in Machine Learning and Artificial Intelligence.
    • 1 year of relevant experience in data analysis (Statistics / Data Science).
    • Experience with one or more general-purpose programming languages, including but not limited to: Java, C / C++, Python, Scala, or R.
    • Experience with one or more of the following topics: Natural Language Processing and Understanding, Classification, Pattern Recognition, and Recommendation Systems. (preferred)
    • Experience working with large datasets, e.g., social network data, scientific data, sensor data, etc. (preferred)
    • Experience in applying machine learning to large datasets. (preferred)
    • Proven programming experience in at least one programming language such as Java, Scala, C++, or a similar object-oriented language. (preferred)

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    What we offer

    • An inspiring and challenging work environment with a flat hierarchy and experienced, helpful colleagues.
    • A comprehensive training and education.
    • Topics we will cover in our training: Big Data Science: Python Machine Learning Libraries (NumPy, SciPy, Pandas, IPython, Scikit-Learn, PyTorch, TensorFlow, JAX, NLTK), Spark for Data Mining and Machine Learning (Spark SQL, Spark MLlib, PySpark).
    • Deep Neural Networks: Feed-Forward Neural Networks, Convolutional Networks, Recurrent Neural Networks, development of production prepares TensorFlow, JAX, and PyTorch solutions.
    • Fundamentals of Data Science and Machine Learning: Time Series and Sequential Data Processing, Supervised and Unsupervised Machine Learning, Classification.
    • Logistic Regression and Random Forest, Support Vector Machines, K-Nearest Neighbors, Naive Bayes, and Gradient Boosting.
    • Generative Deep Learning and LLMs: Training a large language model capable of generating coherent text paragraphs and achieving top performance on many language modeling benchmarks.
    • It also has reading comprehension capabilities and can perform machine translations, answer questions, and create summaries. All of this is done without task-specific training.

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    Topics that you deal with on the job

    Job Locations

    • Location Cologne

      Nordrhein-Westfalen

      Germany

    This is your employer

    Qimia

    Qimia

    Wir sind ein junges und dynamisches Inhabergeführtes IT Unternehmen. Wir unterstützen unsere Kunden durch die Realisierung maßgeschneiderter IT-Lösungen und verbinden dabei Bereiche wie Big Data Analytics, Business Intelligence und Data Warehousing, Cloud Services, Hadoop und Spark, Software Entwicklung in Scala, Python, Java Full Stack Development, Data Migration und gleichzeitig Projekt- und Prozessmanagement.

    Description

  • Company Type
    Established Company
  • Working Model
    Hybrid, Onsite
  • Industry
    Internet, IT, Telecommunication
    • Logo Qimia

    Data Engineer/Data Scientist

    Qimia
    Location
    Cologne
    Working Model
    Onsite
    Diversity
    Open for all genders

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