Senior Applied Machine Learning Engineer
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The role
This role is for a Senior Applied ML Engineer to drive end-to-end ML systems in geospatial, mapping, and recording spaces to enhance fitness experiences.
Own end-to-end AI systems—from prototyping to production deployment, scalable inference, and ongoing maintenance.
Collaborate across product, design, client and server engineering to deploy ML solutions that impact users.
Innovate in AI for fitness by designing novel models for mapping, routing, search, and related features.
Build from rich geospatial and activity datasets using Python/R, PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy; develop data pipelines with Spark, Hadoop, EMR, SQL, Snowflake; and run on SageMaker.
Hybrid work in Berlin with three on-site days per week; own outcomes, raise ML standards, and collaborate to deliver user-centered ML products.
Own end-to-end AI systems—from prototyping to production deployment, scalable inference, and ongoing maintenance.
Collaborate across product, design, client and server engineering to deploy ML solutions that impact users.
Innovate in AI for fitness by designing novel models for mapping, routing, search, and related features.
Build from rich geospatial and activity datasets using Python/R, PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy; develop data pipelines with Spark, Hadoop, EMR, SQL, Snowflake; and run on SageMaker.
Hybrid work in Berlin with three on-site days per week; own outcomes, raise ML standards, and collaborate to deliver user-centered ML products.
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