About this role
About the Role
As a Senior Machine Learning Engineer, you will help build and maintain the fit and sizing models powering our services, impacting 50+ million users across major fashion e-commerce stores in the US and Europe. You will tackle the full ML pipeline from data preparation to productionizing models and monitoring, and you will propose novel ML or non-ML solutions to business problems. What You'll Do
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Participate in product discussions, propose and test solutions to business problems
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Design, build and maintain production machine learning models and pipelines
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Work closely with data and backend engineers to serve predictions, support new products/features
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Productionize data preparation, modeling, prediction, and monitoring
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Analyze large behavioral and product attribute datasets from data prep to productionizing ML models What We're Looking For
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Strong background in machine learning and Python (required)
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Hands-on experience productionizing ML models/pipelines and best practices
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Feature engineering and ML algorithm experience (e.g., Regression, GBM, ANNs), hyperparameter tuning, regularization
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Familiarity with backtesting and time-series techniques
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Version control, unit and integration testing
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Understanding of evaluation metrics for online and offline environments
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Up-to-date with ML techniques and libraries; ability to learn new skills concurrently
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Active use of LLM-powered development tools (e.g., Copilot, Cursor, Claude Code) for coding, testing, and documentation
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Experience with Databricks and/or PySpark in production
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Experience integrating LLMs or embeddings into production systems (e.g., RAG, semantic search, embeddings-based recommendations)
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Basic data visualization to explain problems/solutions
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Communicate effectively in English; collaborate with Data Scientists, Engineers, and Product teams Nice to Have
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Advanced training in ML, Statistics, CS (Masters/PhD preferred)
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Experience with A/B testing as model evaluation
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PySpark and/or Databricks experience
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NLP on unstructured text
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Tooling or systems to support ML investigations/deployments
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Monitoring production model performance with dashboards or visualizations
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Active on GitHub and open-source contributions Compensation & Benefits
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Salary and benefits not specified in posting