MLOPS Architect Machine Learning AI Architect

Position: MLOPS Architect (Machine Learning / AI Architect)

Location: Remote

Duration: 1 Years

Phone & Skype

Client: HCL

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(Scale 110)

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AWS

Python

Airflow

Kedro or Luigi

ML Engineer will enable AI impact at scale by transforming prototypes into productiongrade AI pipelines maintaining models in production and contributing to our AI platform and engineering practices.

1/ Transform prototypes into productiongrade models
Work with data scientists and AI strategists to develop requirements for production models
Design and develop robust applications to manage production models
Collaborate with data governance and technical teams to ensure compliance with Mastercard AI and engineering standards

2/ Maintain models in production
Manage the full CI/CD cycle for live models including testing and deployment
Manage label feedback and model retraining processes
Develop logging alerting and mitigation strategies for handling model errors
Collaborate with data scientists to design and develop drift detection and accuracy measurements for live models

3/ Contribute to AI platform and engineering practices
Collaborate with DS and ML engineering leadership to develop coding standards and practices across the applied AI team
Research test and help train the team on using leading edge AI platforms such as auto ML libraries graph databases and cloud execution frameworks
Contribute to the teams AI infrastructure strategy and management

Required experience
3 years of industry experience in ML engineering
Strong experience in Python
Experience in data product development analytical models and model governance
Experience with AI workflow management tools such as Airflow Kedro or Luigi
Exposure statistical modeling machine learning algorithms and predictive analytics.
Highly structured and organized work planning skills
Strong understanding of the AI development lifecycle and Agile practices
Proficiency in big data technologies like Hadoop Spark or similar frameworks. Experience with graph databases a plus.
Experience in working with cloud computing platforms like AWS Azure or Google Cloud.
Proven track record of delivering data products in environments with strict adherence to security and model governance standards.
Bachelors degree in computer science analytics mathematics statistics economics industrial engineering or physical sciences.