MLOPS Engineer Lead

2 weeks ago

bangalore, India LTIMindtree Full time
Role: MLOps Engineer Lead
· Total Experience: 12 years
Location-Bengelaru
Role Description
Looking for an experienced and motivated GCP evangelist who will work as Lead MLOps Engineer and will be designing, developing, and maintaining the infrastructure and workflows necessary to support the deployment and scaling of multiple concurrent machine learning services. The ideal candidate for this role should has expertise in MLOps, automation, optimisation, and cloud infrastructure which will be essential in scaling our machine learning capabilities and ensuring the reliable and efficient deployment of ML models.
Job Description
• Overall, more than 12 years of experience working as MLOps engineer.
• Design and implement cloud solutions, build MLOps on cloud (AWS, Azure, or GCP)
• Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Circle CI, Airflow or similar tools.
• Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality.
• Data science models testing, validation and tests automation.
• Communicate with a team of data scientists, data engineers and architect, document the processes. Experience in Cloud native skills.
• Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an asset.
• Great communication and presentation skills. Should have experience in working in a fast-paced team culture.
• Design and innovate technical solutions & services for clients requirements.
• Knowledgeable on agile practices.
• ML Model Deployment: Assist in deploying machine learning models into production environments.
• AI ML pipeline and model Monitoring: Contribute to the monitoring and maintenance of model performance and infrastructure health.
• Automation: Participate in the development and maintenance of automated MLOps pipelines
• Collaboration: Collaborate with cross-functional teams to integrate machine learning models into production systems.
• Documentation: Maintain documentation of MLOps processes and procedures.
• Work closely with members of technology teams in the development, and implementation of Enterprise AI platform
• Problem Solving: Assist in troubleshooting and resolving MLOps-related issues.
• Good to have experience with contributing to GitHub and open source initiatives or in research projects
• Ability to quickly, efficiently, and effectively define and prototype solutions with continual iteration within aggressive product deadlines.
• Demonstrate strong communication and documentation skills for both technical and non-technical audiences

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