Applied AI

vor 3 Wochen

Munich, Deutschland AI Futures Vollzeit

As an Applied AI & Lead Machine Learning Engineer you will be at the forefront of combining cutting-edge AI techniques with the company's unique data assets to optimize business decisions and automate processes. You will have the opportunity to advance the state-of-the-art in AI as applied to Finance industry, leveraging the latest research from fields of Natural Language Processing, Computer Vision, and statistical Machine Learning.


Job Responsibilities


  • Build robust Data Science capabilities which can be scaled across multiple business use cases
  • Research and analyse data sets using a variety of statistical and machine learning techniques
  • Communicate AI capabilities and results to both technical and non-technical audiences
  • The role is initially that of an individual contributor, though there will be optional opportunity for management responsibility dependent on the candidate’s experience.
  • German preferred but not required


Required Qualifications & Skills


  • Hands on experience in an ML engineering role
  • MSc (preferred PhD) in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics
  • Track record of developing, deploying business critical machine learning models
  • Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc
  • Experience monitoring, maintaining, enhancing existing models over an extended time period
  • Specialism in NLP or Computer Vision
  • Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.)
  • Extensive experience with pytorch, numpy, pandas
  • Knowledge of open source datasets and benchmarks in NLP / Computer Vision
  • Able to communicate technical information and ideas at all levels; convey information clearly and create trust with stakeholders.


The client is offering a top end industry salary, hybrid working and more. Happy to share further details on a call.

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