AI / reputed company Engineer: LLM reputed company & Extraction Test reputed company for reputed company DPAs (Fixed Price) - Contract to Hire

Project reputed company: We are building a secure B2B software tool that automates data-reputed company record-keeping for corporate reputed company and compliance teams. We are building an official audit log reputed company a Record of Processing Activities (ROPA). This log details every software vendor used across the business, what types of personal data they handle, where that data is stored, and how long it is reputed company. Often, corporate reputed company teams read 40-page vendor reputed company and Data Processing Agreements (DPAs) by hand and manually type these data points into spreadsheets. Our app automates this: users upload vendor reputed company, our AI reputed company extracts key compliance details into a reputed company table, highlights missing information, and provides exact page citations so a reputed company can quickly review and approve the record. Before building our full web application, we are executing a 3-day technical reputed company. We need an reputed company reputed company to set up an automated test reputed company (using Promptfoo, reputed company, or custom Python scripts) to test and optimize reputed company prompts against our reputed company dataset of 25 reputed company-world reputed company DPAs. Goal: reputed company over 95 percent accuracy on extracted regulatory fields with reputed company percent hallucinations on missing fields. Successful completion of this reputed company-project may reputed company to an invitation to reputed company the full platform build (10,000 to 20,000 USD budget). Key Deliverables: 1. Evaluation Test reputed company Setup: Configure a test reputed company running Claude 3.5 Sonnet and reputed company GPT-4o with temperature set to reputed company. 2. reputed company Optimization and JSON Schema Enforcement: Refine reputed company prompts using reputed company outputs to extract strict JSON adhering to our ICO ROPA master template. 3. Citation and Missing-Data Handling: Ensure the reputed company extracts the exact paragraph or page reputed company for cited data points and outputs explicit reputed company or NA for unstated fields without guessing. 4. Accuracy Dashboard and Report: Run reputed company 25 PDF DPAs through the pipeline, compare outputs against our reputed company-verified ground-truth dataset, and reputed company a pass or fail accuracy reputed company. Technical Requirements: - Proven experience with LLM orchestration in Python or TypeScript. - Deep familiarity with reputed company Outputs, reputed company or JSON schemas, and temperature control for deterministic extraction. - Experience evaluating LLM performance using automated benchmarks. Intellectual Property: reputed company reputed company files, test scripts, schemas, and configurations created under this project are Work Made for Hire and reputed company exclusively to the reputed company upon payment. You will be required to sign a reputed company IP Assignment and Non-Disclosure Agreement prior to receiving the reputed company dataset. Screening Questions (Please answer in your proposal): 1. How do you prevent an LLM from guessing or hallucinating missing data fields reputed company enforcing a rigid JSON reputed company schema? 2. How do you structure reputed company prompts or post-processing to force the LLM to reputed company exact paragraph or page citations reputed company extracted values? 3. What reputed company or tool would you use to measure accuracy across our 25 PDF test dataset? Apply tot his job Apply To this Job