Vetted OCR Professionals

Weston Carpenter

Screened

Mid-level Backend Software Engineer specializing in distributed systems

San Francisco, CA6y exp

“Technical/presales engineer with experience at Grubhub and Appen, spanning LLM-adjacent data labeling workflows and production AI troubleshooting. Built an integrations platform at Grubhub and has hands-on experience diagnosing prompt-related AI failures via Splunk, adding JUnit tests and logging to prevent recurrence. Known for shipping customer-specific workflow adaptations (e.g., OCR annotation coordinate transformations for crop/rotation) while keeping timelines intact through iterative delivery and parallelization.”

“Enterprise NetSuite Financials professional with hands-on ownership of GL configuration, month-end close, reporting, and production support in a multi-subsidiary environment at Bank of America. Particularly strong in stabilizing finance operations under deadline pressure, improving close efficiency, and building audit-ready reporting and controls across NetSuite and integrated systems.”

Neda Bokhari

Screened

Entry-level AI product and data professional specializing in workflow automation

San Francisco, CA1y exp

“Early-stage go-to-market candidate at Retroshift who has owned outreach across users, investors, and prospective clients in a zero-to-one environment. They’ve helped onboard 20+ alpha users and pushed the company into 3+ accelerator interview processes, showing strong traction-building ability through scrappy, multi-channel outbound.”

Yuchen Wang

Screened

Intern Software Engineer specializing in full-stack development and AI/ML

New York, NY1y exp

“Built and maintains an AI Finance Tracker end-to-end as a solo full-stack product owner, from Figma designs and React frontend to Flask APIs, Firestore, auth, deployment, and AI insights. Stands out for combining product instinct with pragmatic engineering decisions like pre-aggregating financial data to control LLM costs and adding OCR receipt scanning based on real user feedback.”

Rami Jaloudi

Screened

Senior Applications Engineer specializing in legal technology and eDiscovery

New York, NY16y exp

“Early-stage founder candidate exploring an AI-enabled legal tech startup focused on document intelligence, secure workflows, and enterprise automation. Brings a rare blend of technical architecture fluency and product/business thinking, with clear firsthand insight into legal and document-heavy operational pain points.”

“Founding engineer at an edtech startup who combines hands-on engineering leadership with advanced AI-native development workflows. They’ve built an AI grading pipeline and a multi-agent SDLC tool, and stand out for treating AI agents like an engineering team with planning, parallel execution, QA, and rigorous validation.”

“Built and deployed an LLM-powered customer support assistant (“Notable Assistant”) focused on automating common post-customer queries while maintaining multi-turn context and meeting scalability/latency needs. Experienced with production orchestration and operations using Kubernetes and Apache Airflow (DAG-based ETL, scheduling, monitoring/alerts), and has partnered closely with customer service stakeholders to align chatbot behavior with brand voice through iterative testing.”

“Applied NLP/ML engineer with experience at KeyBank and Novartis building production document intelligence and entity-resolution systems in finance and healthcare. Has delivered end-to-end pipelines (Airflow + AWS) using transformers (DistilBERT/Sentence-BERT), vector search (FAISS/Milvus/Pinecone), and human-in-the-loop labeling to achieve measurable gains (40%+ faster queries; up to 88% F1 and 93% precision/90% recall in entity linking).”

Janvitha Mandyam

Screened

Mid-level AI/ML Engineer specializing in Generative AI and NLP

Chicago, IL4y exp

“GenAI/LLMOps practitioner who deployed a production RAG-based customer service and knowledge retrieval system for a global bank using LangChain, FAISS/Azure Cognitive Search, GPT-4/Claude, and Guardrails—driving a reported 35% Q&A accuracy lift while reducing handle time and escalations. Also partnered with non-technical leaders at CVS Health to deliver ML-driven supply chain risk and inventory insights via anomaly detection, NLG summaries, and stakeholder-friendly dashboards.”