Large Language Model Operations Leader

15 hours ago

Mysore, Karnataka, India beBeeLeadership Full time ₹ 18,00,000 - ₹ 25,20,000

We are seeking a seasoned LLM Operations Leader to spearhead the deployment, scaling, and monitoring of large language models in production.

This role will focus on designing and implementing robust, scalable, and secure infrastructure for managing the end-to-end lifecycle of LLMs—from training and fine-tuning to inference and continuous improvement.

The ideal candidate will have hands-on expertise with MLOps frameworks, cloud-native architectures (preferably Azure), and modern DevOps practices, combined with leadership skills to align cross-functional stakeholders and establish best practices for LLM operations.

  • Develop and implement LLM Ops infrastructure for training, fine-tuning, and large-scale inference.
  • Establish and enforce 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.
  • Create 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.

We offer a competitive compensation package, performance-based incentives, and health benefits. We believe in your continuous growth and provide company-sponsored certifications, training programs, and skill-building opportunities to help you succeed. We foster a culture of inclusivity and support, with remote work options and a fully supported work-from-home setup to ensure your comfort and productivity. Our positive and inclusive culture includes team activities, wellness and mental health programs to ensure you feel supported.

Key Responsibilities:
  • Lead LLM Ops Infrastructure Development: Design and implement scalable, secure, and efficient infrastructure for LLM training, fine-tuning, and inference.
  • Establish Best Practices: Develop and enforce guidelines for model deployment, monitoring, retraining, and continuous improvement.
  • Ensure Safe and Ethical LLM Usage: Implement security, compliance, and responsible AI guardrails to guarantee safe and ethical LLM usage.
  • Streamline LLM Lifecycle: Collaborate with data science, research, and product teams to optimize the LLM lifecycle.

Benefits:

  • Competitive compensation package
  • Performance-based incentives
  • Health benefits
  • Company-sponsored certifications, training programs, and skill-building opportunities

Culture:

  • Inclusive and supportive work environment
  • Remote work options
  • Full support for work-from-home setup
  • Team activities, wellness and mental health programs

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