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Senior Machine Learning Engineer - Maps

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Uber

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Location:
Netherlands , Amsterdam

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

The Places Data Team owns Uber's "Ground Truth" — the definitive dataset of POIs, Addresses, Building Footprints, and Entrances that powers the core of every journey: the beginning and the end. Without accurate place data, a ride doesn't start, and a courier can't deliver. We operate at massive scale (billions of places), solving inference and conflation problems using ML to match and summarize data from dozens of providers. As a Senior ML Engineer, you'll build production ML systems focusing on places matching, attributes inference, summarization, friction detection, etc.

Job Responsibility:

  • Design, develop and productionize end-to-end ML solutions for places data conflation (POI, addresses, BFP, etc.) and attribute inference using a mix of classical ML, deep learning, and generative AI
  • Collaborate with product, science, and engineering teams to execute on the technical vision and roadmap
  • Conduct rigorous experimentation and A/B testing to validate model performance and iterate on improvements
  • Own projects from initial mathematical formulation through to prototyping, algorithm implementation, and large-scale experimentation in production
  • Raise the technical bar for the team. You will mentor L3/L4 engineers, lead complex code reviews, and foster a culture of engineering excellence and scientific rigor

Requirements:

  • Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
  • 4+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments, delivering measurable business impact over multiple quarters and making significant technical contributions
  • Proficiency in programming languages such as Python, Scala, Java, or Go
  • Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
  • Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps

Nice to have:

  • Deep understanding of CS fundamentals, software engineering principles, and modern development methodologies
  • Direct experience in GIS, matching algorithms
  • Expertise in large-scale data systems like Spark, Hive, and Presto
  • Experience building and optimizing gradient boosting and deep learning models
  • Background in Optimization or Causal Inference applied to business problems
  • Exceptional problem-solving, critical thinking, and communication skills, with the ability to influence leadership and present complex technical trade-offs to non-technical stakeholders

Additional Information:

Job Posted:
March 21, 2026

Work Type:
On-site work
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