Senior Machine Learning Engineer - (Logistics, Optimization)

Delivery Hero
Berlin
Workplace: HybridFull timeFunction: Data Science & Machine LearningSkills: ["Communication"]

Build and maintain scalable machine learning model services for real-time vehicle routing and efficient order assignment, directly improving logistics performance and customer satisfaction metrics. You’ll design robust ML infrastructure, develop tooling across model development, monitoring, serving, and experimentation, and collaborate closely with data scientists and engineers. The role leverages modern cloud infrastructure and evaluates new technologies to expand the team’s optimization capabilities.

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FursaFursa
Delivery Hero
Delivery Hero
2 days ago

Senior Machine Learning Engineer - (Logistics, Optimization)

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Build and maintain scalable machine learning model services for real-time vehicle routing and efficient order assignment, directly improving logistics performance and customer satisfaction metrics. You’ll design robust ML infrastructure, develop tooling across model development, monitoring, serving, and experimentation, and collaborate closely with data scientists and engineers. The role leverages modern cloud infrastructure and evaluates new technologies to expand the team’s optimization capabilities.
Location: Berlin
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design, build, and maintain scalable ML model services optimized for performance and efficiency.
  • •Build robust architecture/infrastructure for critical model inputs feeding a dispatch algorithm used for real-time routing decisions.
  • •Collaborate with data scientists and engineers to understand product needs and deliver scalable solutions.
  • •Develop and enhance ML engineering tooling for model development, monitoring, serving, and experimentation.
  • •Use cloud infrastructure to build highly available systems and proactively suggest new technologies and architectures for new use cases.

Pay and Benefits

Equity and Bonus:Equity
Perks:Paid LeaveLearning BudgetGym MembershipInsurancePensionEquity

Key Requirements

  • •4+ years of ML engineering or MLOps experience, including hands-on work with model serving, training, experimentation, and feature engineering.
  • •3+ years designing and implementing machine learning models (e.g., regression, classification, tree-based ensembles) to solve real-world business problems, with a strong foundation in statistics and probability.
  • •Experience building infrastructure and applications around machine learning pipelines using modern programming languages, including Python.
  • •Ability to evaluate technologies for business problems and propose solutions using pros/cons analysis.
  • •Fluency in English with clear written and verbal communication.
Experience:ML engineeringMLOpsReal-time routingMachine learning pipelines
Skills:Communication
Languages:English
Tech Stack:PythonAWSGoogle CloudMetaflowAirflowMLflowArgo WorkflowsDockerKubernetesHelmTerraformCI/CD

Company Brief

Delivery Hero
Global online food-ordering and local delivery platform operating multiple regional brands (e.g., Foodpanda, Glovo, Talabat) across 50–70+ countries, supplying food and quick-commerce deliveries via marketplace and logistics services.
Industry: Online Marketplaces
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Berlin, Germany
Founded: 2011
Glassdoor
Glassdoor: 3.4
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