MLOPS Architect Job Torrance area,California USA,IT/Tech

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

1. Transform prototypes into production-grade 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 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 Client 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 Client libraries, graph databases, and cloud execution frameworks

Contribute to the team's AI infrastructure strategy and management

Required experience

3+ years of industry experience in Client 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 to 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.

Bachelor's degree in computer science, analytics, mathematics, statistics, economics, industrial engineering, or physical sciences.