Posted:1 day ago|
Platform:
On-site
Full Time
- Infrastructure Management: Build scalable and robust infrastructure for ML models, ensuring seamless production integration.
- CI/CD Expertise: Develop and maintain CI/CD pipelines with a focus on ML model deployment.
- Model Deployment and Monitoring: Deploy ML models using TensorFlow Serving, Pytorch Serving, Triton Inference Server, or TensorRT and monitor their performance in production.
- Collaboration: Work closely with data scientists and software engineers to transition ML models from research to production.
- Security and Compliance: Uphold security protocols and ensure regulatory compliance in ML systems.
- Proficiency in Docker and Kubernetes for containerization and orchestration.
- Experience with CI/CD pipeline development and maintenance.
- Experience in deploying ML models using TensorFlow Serving, Pytorch Serving, Triton Inference Server, and TensorRT.
- Experience with cloud platforms like AWS, Azure, and GCP.
- Strong problem-solving, communication, and teamwork skills.
- Bachelor’s/Master’s degree in Computer Science, Engineering, or a related field.
- 4-6 years of experience in ML project management, with a recent focus on MLOps.
- AI Technologies Deployment, Data Engineering, IT Performance, Scalability Testing, and Security Practices.
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