LLMOps Engineer - Cloud/Gen AI

Vertiv-posted about 1 year ago
Full-time
Westerville, OH
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As an LLMOps Engineer - Cloud/Gen AI at Vertiv Corporation, you will be responsible for building and maintaining the infrastructure and pipelines for Large Language Models (LLMs). This role involves automating and streamlining the LLM lifecycle to ensure the efficiency, scalability, and reliability of Generative AI models in production. You will work closely with Generative AI Architects and other teams to optimize model performance and resource utilization, while also overseeing cloud infrastructure specifically for LLM workloads.

  • Conceptualize, develop, and execute Machine Learning (ML)/LLM pipelines for Large Language Models, including data acquisition, pre-processing, model training/tuning, deployment, and monitoring.
  • Utilize automation tools such as GitOps, CI/CD pipelines, and containerization technologies (Docker, Kubernetes) to streamline ML/LLM tasks across the lifecycle.
  • Establish robust monitoring and alerting systems to track LLM performance, data drift, and other key metrics, proactively identifying and resolving issues.
  • Perform truth analysis to assess the accuracy and effectiveness of LLM outputs, comparing them to known, accurate data.
  • Collaborate closely with infrastructure, DevOps teams, and Generative AI Architects to optimize model performance and resource utilization.
  • Oversee and maintain cloud infrastructure (e.g., AWS, Azure) for LLM workloads, ensuring cost-efficiency and scalability.
  • Stay current with the latest advancements in ML/LLM Ops, integrating these developments into generative AI platforms and processes.
  • Communicate effectively with both technical and non-technical stakeholders, providing updates on the performance and status of LLMs.
  • Bachelor's or Master's degree in Computer Science, Engineering or similar.
  • At least 5 years of experience as an ML engineer within public cloud platforms.
  • Strong programming skills in Python and/or other languages.
  • Expertise in cloud platforms (e.g., AWS, Azure) for ML workloads, MLOps, DevOps, or Data Engineering.
  • Proven experience in MLOps, LLMOps, or related roles, with hands-on experience deploying and managing machine learning and LLM pipelines.
  • Familiarity with generative AI applications and domains such as content creation, data augmentation, style transfer.
  • Strong knowledge of Generative AI architectures and methods, including chunking, vectorization, context-based retrieval and search, working with LLMs such as Open AI GPT 3.5/4.0, Llama2, Llama3, Mistral.
  • Strong understanding of cybersecurity principles and best practices to ensure data integrity, security, and confidentiality.
  • Knowledge of AI ethics and understanding how to apply Trustworthy AI for safe, responsible, and ethical use of AI technology.
  • Experience with data engineering and data visualization tools and techniques.
  • Passion for learning and exploring new generative AI technologies and methods.
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