Match Score
Against your primary resumeLogin to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Protocol Intelligence
Data-driven signals on your job's competitivenessLog in to see why each signal reads the way it does.
Job Description
Structured overview of role & requirementsAbout This Role
Lead design and implementation of end-to-end MLOps and LLMOps pipelines including model development, training, deployment, and monitoring in production.
Develop automation for scalable, efficient, and cost-effective deployment and management of large language models in cloud environments.
Build and maintain CI/CD pipelines, data pipelines, model monitoring systems, and optimize deployed AI model performance with hardware acceleration.
Minimum Requirements
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field.
5+ years of experience in MLOps, with at least 2 years specifically working with LLMOps pipelines for large language models.
Proven experience in deploying and managing machine learning models at scale in cloud environments (AWS, GCP, Azure).
Mandatory skills include expertise in cloud platforms, containerization (Docker, Kubernetes), CI/CD tools, ML frameworks (TensorFlow, PyTorch, Hugging Face), data engineering pipelines, and model monitoring tools.
Ideal Candidate Profile
Experienced in managing large language model operations end-to-end, including pipeline orchestration and performance optimization.
Skilled at integrating AI model workflows with cloud infrastructure and automation tooling to ensure scalable production deployment.
Strong knowledge and hands-on experience with security, governance, and compliance aspects of AI systems including model lifecycle management.