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LIlimango

Machine Learning Engineer – Retail & Buying(m/w/x)

München
Full-timeWith Home OfficeSenior
AI/ML

Developing dynamic pricing and demand forecasting models for online retail, including LLM exploration. End-to-end ML systems in production experience required. Hybrid work, creative freedom.

Requirements

  • Proven experience as Machine Learning Engineer (mid–senior)
  • End-to-end ML systems in production experience
  • Strong command of Python
  • Strong command of SQL
  • Practical experience with ML frameworks (TensorFlow, scikit-learn, XGBoost, LightGBM)
  • Model training, tuning, and deployment experience
  • Hands-on experience with GCP ML services
  • Familiarity with Apache Airflow
  • Fluency in English
  • Domain knowledge in retail, e-commerce, or supply chain
  • Experience building production time-series models
  • Understanding of ETL/ELT pipelines
  • Understanding of MLOps practices
  • Understanding of CI/CD for ML
  • Understanding of feature stores
  • Understanding of model monitoring
  • Hands-on experience with Large Language Models
  • Prompt engineering experience
  • LLM fine-tuning or integration experience
  • Strong analytical reasoning
  • Structured approach to designing ML solutions
  • Curiosity and willingness to experiment with emerging technologies
  • Ability to explain complex ML concepts to non-technical stakeholders
  • Proactive, ownership-driven mindset
  • Focus on delivering reliable production systems
  • Comfort working with incomplete information
  • Comfort working with evolving requirements
  • Comfort working with iterative discovery
  • Team-oriented attitude
  • Openness to code reviews
  • Openness to architectural discussions
  • Openness to collaborative problem-solving

Tasks

  • Design and develop advanced machine learning solutions
  • Maintain and optimize ML models at scale
  • Build models for dynamic pricing and demand forecasting
  • Implement data-driven buying decisions
  • Explore and implement LLM-based methods
  • Enhance automation and decision support
  • Improve model interpretability in real retail scenarios
  • Build reliable and scalable data pipelines
  • Ensure high-quality data flows across ML ecosystem
  • Collaborate with business stakeholders and product teams
  • Translate complex retail challenges into measurable ML outcomes
  • Ensure models deliver tangible business value

Work Experience

  • approx. 4 - 6 years

Education

  • Bachelor's degreeOR
  • Master's degree

Languages

  • EnglishFluent

Tools & Technologies

  • Python
  • SQL
  • TensorFlow
  • scikit-learn
  • XGBoost
  • LightGBM
  • Google Cloud Platform (GCP)
  • Cloud Storage
  • BigQuery
  • Vertex AI
  • Cloud Functions
  • Apache Airflow
  • Large Language Models (LLMs)

Benefits

Flexible Working

  • Hybrid working model
  • Remote working

Informal Culture

  • Open, team-oriented atmosphere
  • Creative freedom

Parking & Commuter Benefits

  • Centrally located office

Learning & Development

  • Language courses
  • Tailored development programs

Public Transport Subsidies

  • Subsidized MVG ticket

Healthcare & Fitness

  • EGYM Wellpass

Company Bike

  • JobBike

Team Events

  • Company events
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of limango and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.

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