Lead ML/Ops Engineer (Azure Data Factory)
Gravity IT Resources
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Position Title: Lead ML/ Ops Engineer (Azure Data Factory)
Position Type: 4-month contract
Location: Remote
Work Authorization: U.S. Citizen or Green Card Holders only
Referral Fee: $225 +/- per month based on hours worked.
Position Overview:
The Machine Learning team at our client is responsible for architecting the productionized solution around rules-based and AI/ML models to integrate predictions seamlessly into the business processes, ensuring governance, resiliency, explainability, reproducibility, scalability of the models.
We are looking for a highly capable MLOps Engineer with Software Engineering background to optimize and refactor rules-based and machine learning systems built on Databricks and Azure Data Factory
Responsibilities:
- Convert and consolidate existing Revenue Management solutions into reusable cross-branded framework/ python package- including documentation and testing of package functions.
- Automate production deployments incorporating MLOps best practices.
- Developing alerting tool frameworks for monitoring production model performance and effectiveness.
Required Skills:
- 5+ years of overall experience in Data Analytics.
- 2+ years of experience with ML Engineering and/or MLOps.
- Bachelor’s degree in computer science, data science, mathematics, or a related field.
- Experience Agile Software Development.
- Experience in a large corporation or consulting firm.
- Experience with IoT and/or sensor data.
- Experience building scalable machine learning systems and data-driven products working with cross-functional teams.
- Well-developed software engineering fundamentals, including use of proper development, QA, and production environments, and the ability to write production-level code when needed.
- Experience creating python package.
- Proficiency in Python and experience with common data analytics packages (e.g. Numpy, Pandas, Sklearn, PySpark).
- Proficiency in Databricks, Azure Data Factory, and MLFlow.
- Proficiency in SQL.
- Good communication skills and the ability to understand & synthesize requirements across multiple project domains.
- Works effectively with cross-functional teams.