Description

You will operationalize complex machine learning models into production and manage end-to-end deployment.

Responsibilities

• Deploy and scale models and algorithms by collaborating with data science and engineering teams.
• Design, develop, and maintain adaptable data pipelines for use-case specific data.
• Integrate ML use cases into business pipelines and coordinate with upstream and downstream teams.
• Develop and maintain pipelines to publish model performance metrics for model review cadences.
• Support operationalized models and create runbooks for ongoing maintenance.

Required Skills

• 10+ years of experience in machine learning or related engineering roles.
• Proficiency with standard machine learning algorithms including Regression and Classification.
• Experience with Natural Language Processing concepts such as sentiment generation, topic modeling, and TFIDF.
• Working knowledge of scikit-learn, vader sentiment, pandas, and PySpark.
• Ability to design and maintain end-to-end deployment pipelines.
• Experience generating and publishing model performance metrics for risk oversight.
• Background in developing maintenance runbooks for production models.

Key Skills

Education

Any Gradute