Description:
Digital technologies, including analytics and AI, give companies a once-in-a-generation opportunity to perform orders of magnitude better than ever before. But clients need new business models built from analyzing customers and business operations at every angle to really understand them.
With the power to apply artificial intelligence and data science to business decisions via enterprise data management solutions, we help leading companies prototype, refine, validate and scale the most desirable products and delivery models to enterprise scale within weeks
Job Description
- Provide thought leadership around MLOPs and ML Best Practices
- Interpret AI Policy and Framework into MLOPs Architecture and guide implementation
- Design the data pipelines and engineering infrastructure to support enterprise machine learning systems at scale
- Develop and deploy scalable tools and services to handle machine learning training and inference
- Identify and evaluate new technologies to improve performance maintainability and reliability of the machine learning systems
- Apply software engineering rigor and best practices to machine learning including CI/CD automation etc.
- Support model development with an emphasis on auditability versioning and data security
- Facilitate the development and deployment of proof-of-concept machine learning systems
- Communicate with stakeholders to build requirements and track progress
Skillset:
- Expert knowledge of MDLC and Industry Best Practices around it & feature engineering
- Experience in model deployment both on batch and real time models
- Exposure in measuring model training and enable modelers to store and track model training runs.
- Functional knowledge of the interplay between Model Governance Change and Release Management
- Experience building end-to-end systems as a Platform Engineer ML DevOps Engineer or Data Engineer (ETL/ ELT)
- Strong software engineering skills in RDMS Sql Pyspark etc.
- Fluency in Python SAS good to have
- Comfort with Linux administration
- Experience working with cloud computing and database systems Snowflake is a plus
- Experience building custom integrations between cloud-based systems using APIs real time data pipeline