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2 weeks ago
We are seeking a seasoned expert in large language model operations to spearhead the deployment, scaling, and monitoring of AI models in production.
This critical role will focus on crafting robust, scalable, and secure infrastructure for managing the end-to-end lifecycle of LLMs, driving business value through efficient AI operations.
Key Responsibilities- Design and implement LLM ops infrastructure for training, fine-tuning, and large-scale inference.
- Establish best practices for model deployment, monitoring, retraining, and continuous improvement.
- Implement security, compliance, and responsible AI guardrails to ensure safe and ethical LLM usage.
- Collaborate closely with data science, research, and product teams to streamline the LLM lifecycle.
- Build and manage ops automation pipelines for dataset updates, retraining, and model versioning.
- Evaluate and implement tools for cost optimization and performance tuning in large-scale environments.
- Provide technical leadership and mentor teams on LLMOps methodologies.
- Strong background in LLM deployment, scaling, and monitoring.
- Proficiency in MLOps frameworks (Kubeflow, MLflow, Databricks deployment patterns).
- Hands-on experience with cloud-native architectures.
- Strong expertise in CI/CD pipelines, containerization, and microservices.
- Solid understanding of observability tools.
- Deep knowledge of model evaluation, drift detection, prompt management, and AI safety guardrails.
- Programming expertise in Python and Bash scripting.
- Experience with vector databases and RAG pipelines.
- Strong leadership and stakeholder communication skills.
- Knowledge of LLM safety, bias mitigation, and regulatory compliance.
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