Senior Manager, Applied ML—Search & NLP (Hybrid)

Grainger; Lake Forest (IL); Hybrid; USD 214,000 - 268,000; Full time

Job summary

Grainger in Lake Forest, IL seeks a Manager, Applied Machine Learning to design scalable ML architectures for search, information retrieval, and relevance using Python, Solr, FAISS, and NLP techniques. You will develop and deploy models for ranking and recommendations, leveraging clickstream and catalog data in a hybrid work setting.

Responsibilities include building feature pipelines with SQL, Spark, and Python, developing real-time query suggestions, and deploying models via FastAPI/Flask with

Qualifications

• Bachelor's degree in data science, CS, engineering or related field plus 5 years of related experience.
• Experience designing scalable ML architectures for search and ranking.
• Experience with NLP for query understanding and search relevance.

Responsibilities

• Design scalable machine learning architectures for search, information retrieval, and relevance using Python, Solr, and FAISS.
• Develop NLP applications for query understanding, classification, and search relevance.
• Develop and implement ML models for search ranking using clickstream and catalog data.
• Design feature pipelines using SQL, Python, Spark for ML models.
• Build real-time typeahead/autocomplete systems from clickstream and behavior data.
• Deploy ML systems with training, low-latency inference, and monitoring on-premise and cloud.

Skills

Python

NLP

Transformers

Query understanding

Search relevance

Python-based ML

FAISS

APIs

Education

Bachelor's degree in Data Science/CS/Engineering or related field

Tools

FastAPI

Flask

Docker

Kubernetes

Apache Spark

FAISS

Job description

Grainger in Lake Forest, IL seeks a Manager, Applied Machine Learning to design scalable ML architectures for search, information retrieval, and relevance using Python, Solr, FAISS, and NLP techniques. You will develop and deploy models for ranking and recommendations, leveraging clickstream and catalog data in a hybrid work setting.

Responsibilities include building feature pipelines with SQL, Spark, and Python, developing real-time query suggestions, and deploying models via FastAPI/Flask with