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Esha Pahwa
Intern Machine Learning Engineer specializing in LLM agents and multimodal reasoning
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About
LLM/agent engineer who built a production code-generation agent at Corvic AI that lets non-technical users query CSV/tabular data in natural language by generating and executing Python. Focused on making LLM systems reliable and scalable via schema-aware validation, sandboxed execution-feedback retries, prompt caching/embeddings, async execution, and high-throughput data processing with Polars; also partnered with Adobe product/marketing to ship brand-aligned AI content generation for email and push notifications.
Experience
Education
Key Strengths
- Built and deployed an LLM code-generation agent for natural-language querying of structured data
- Reliability engineering for LLM outputs via schema-aware validation loops and execution-feedback retries
- Scalability optimization using prompt caching, embeddings, async components, and Polars for large CSV throughput
- Strong orchestration experience with LangChain and Ray for tool coordination and parallelization
- Evaluation rigor: explicit metrics (accuracy/latency), modular testable design, unit + end-to-end replay tests, human-in-loop reviews
- Pragmatic model/retrieval/prompt selection using small eval sets, baseline benchmarking, and iterative A/B testing
- Effective collaboration with non-technical stakeholders to translate LLM behavior into brand/personalization requirements
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