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MLOps Engineer
Not specifiedFull-timeAI & Machine LearningFinancial Services
Join the Data, AI, and ML teams of a financial organization to build, deploy, and operate production machine learning solutions and evolve its enterprise ML platform.
Responsibilities
- Design architectures for machine learning solutions and lead their production deployment.
- Develop and maintain MLOps and CI/CD pipelines.
- Build infrastructure that helps data science teams develop, deploy, and operate models reliably.
- Establish scalable processes for model deployment, versioning, monitoring, and lifecycle management.
- Develop and maintain services and APIs that support machine learning solutions.
- Contribute to the development and evolution of the organization's ML platform.
- Work with data science, data engineering, DevOps, architecture, cybersecurity, and infrastructure teams.
- Support the implementation and operation of generative AI solutions.
Requirements
- At least 3 years of experience in MLOps, ML engineering, or deploying and operating machine learning models in production.
- Hands-on experience with AWS, Python, Bash, Docker, and Git.
- Experience with CI/CD and developing and maintaining services or APIs that support machine learning models.
- Experience with model deployment, versioning, and monitoring.
- Ability to work effectively with data science, data engineering, and DevOps teams.
- Ability to own machine learning solutions from architecture and design through production deployment.
Nice to have
- Experience with GitHub Actions.