Description

Deploy and scale machine learning models in production by bridging data science and engineering.

This role is on-site.

Responsibilities

• Operationalize complex machine learning models through end-to-end deployment.
• Design and maintain adaptable data pipelines for specific use cases.
• Integrate ML use cases into business pipelines by collaborating with upstream and downstream teams.
• Develop pipelines to generate and publish model performance metrics for review cadences.
• Support operationalized models and create maintenance runbooks.

Required Skills

• 10+ years of professional experience.
• Deep understanding of standard Machine Learning algorithms including Regression and Classification.
• Experience with NLP concepts such as sentiment generation, topic modeling, and TFIDF.
• Working knowledge of scikit-learn, vader sentiment, pandas, and PySpark.
• Proficiency in Data Science workflows and model scaling.
• Ability to collaborate with data science and engineering teams to deploy algorithms.

Preferred Skills

• Experience with PySpark and TF-IDF implementation at scale.
• Background in Data Science workflows.

Key Skills

Education

Any Gradute