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ML/DL Engineer

4 tygodni temu

Warszawa, Mazovia, Polska Fetcherr Pełny etat

Machine Learning / Deep Learning Engineer

Fetcherr experts in deep learning, algo-trading, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions.

We are seeking a talented senior machine learning engineer / data scientist to help us advance our machine learning capabilities. The ideal candidate should be a self-driven, motivated, and independent thinker who is passionate about using data and machine learning to drive business outcomes.

Responsibilities:
  • Develop and implement cutting-edge machine learning models and algorithms for demand forecasting applications.
  • Conduct research and experimentation to identify and evaluate new approaches for improving model accuracy and performance.
  • Collaborate with cross-functional teams, including business stakeholders, data engineers, and software developers, to deploy and maintain machine learning systems in production.
  • Mentor and train junior team members, promoting best practices and fostering a culture of continuous learning and improvement.
  • Communicate technical findings and insights to non-technical stakeholders, including executives and other decision-makers.
Requirements:

You'll be a great fit if you have:

  • 3+ years of hands-on experience in data science and machine learning.
  • Expertise in time-series forecasting, with experience working in demand forecasting or related contexts.
  • Strong coding skills in Python and SQL, with experience using related open-source libraries and frameworks, including TensorFlow/PyTorch and Pandas.
  • Experience building tabular machine learning models using gradient boosting methods and deep learning.
  • Strong understanding of machine learning systems in production, including good coding practices for testing, reproducibility, and version control.
  • Excellent written and verbal communication skills.
Nice to have:
  • Degree in Computer Science, Statistics, or related quantitative field.
  • Published papers, patents, or professional posts.
  • Experience in leveraging deep learning and machine learning in domains such as finance/trading, reinforcement learning, or natural language processing.
  • Experience with MLOps and cloud platforms like GCP.
  • Experience with workflow orchestration tools like Apache Airflow or Dagster to schedule and monitor machine learning workflows.
  • Strong data visualization and data analysis skills.
  • Knowledge of code optimization, cloud computing, containerization, and continuous integration/continuous deployment (CI/CD) pipelines.
  • Competitive programming and data science (Kaggle like) experience.
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