Senior ML Engineer

Our expectations of the ideal candidate: 

• 5+ years of machine learning engineering experience
• 3+ years of them building and deploying deep learning models in production
• Experience with search, NLP, ranking, recommendation, or relevant systems
• Expert-level proficiency in Python and its core data science libraries and SQL (e.g., PySpark, Pandas, NumPy, Scikit-learn, PyTorch)
• The ability to design an ML system from scratch in at least one area, including data analysis, annotation, and processing through to a model serving in production
• Experience turning a business goal into an ML problem with the right proxy metrics and non functional requirements, and designing or substantially contributing to the A/B tests and statistical evaluation that prove impact on user behavior
• Experience using MLOps tools and practices to manage the ML model lifecycle
• Experience deploying models to production on ML serving infrastructure and optimizing for latency, and awareness of concept drift and how to detect and manage it

Nice to have:

• An academic background in a quantitative field such as Computer Science, Mathematics, or a related discipline will be a plus
• Experience fine tuning and deploying large language models (or small language models), for query understanding or relevance
• Subject matter depth in geocoding or autocomplete relevance specifically
• Experience in mapping, location, or geospatial products
• Experience building for developing markets, where the underlying map and address data is weak
• Experience with BigQuery or Databricks certifications
• Subject matter depth in search, geocoding, ranking, or recommendation systems

English: Upper-Intermediate 

Soft skills:

• The ability to influence teammates and partner teams, and to communicate complex results clearly

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