LLM Ops Engineer

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Role Overview :-

Monitor, evaluate, and optimize AI/LLM workflows in production environments. Ensure reliable, efficient, and high-quality AI system performance by building out an LLM Ops platform that is self-serve for the engineering and data science departments.

Key Responsibilities:-

• Collaborate with data scientists and software engineers to integrate an LLM Ops platform (Opik by CometML) for existing AI workflows
• Identify valuable performance metrics (accuracy, quality, etc) for AI workflows and create on-going sampling evaluation processes using the LLM Ops platform that alert when metrics drop below thresholds
• Cross-team collaboration to create datasets and benchmarks for new AI workflows
• Run experiments on datasets and optimize performance via model changes and prompt adjustments
• Debug and troubleshoot AI workflow issues
• Optimize inference costs and latency while maintaining accuracy and quality Develop automations for LLM Ops platform integration to empower data scientists and software engineers to self-serve integration with the AI workflows they build

Requirements:-

• Strong Python programming skills
• Experience with generative AI models and tools (OpenAI, Anthropic, Bedrock, etc)
• Knowledge of fundamental statistical concepts and tools in data science such as: heuristic and non-heuristic measurements in NLP (BLEU, WER, sentiment analysis, LLM-as-judge, etc), standard deviation, sampling rate, and a high level understanding of how modern AI models work (knowledge cutoffs, context windows, temperature, etc)
• Familiarity with AWS
• Understanding of prompt engineering concepts
• People skills: you will be expected to frequently collaborate with other teams to help to perfect their AI workflows

Experience Level 3-5 years of experience in LLM/AI Ops, MLOps, Data Science, or MLE

Pattern is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.