Vetted Natural Language Processing Professionals

Jarin Tasnim

Screened

Staff/Lead Software Engineer specializing in distributed data and ML platforms

Mountain View, CA6y exp

“Defense-domain AI engineer who built a production ReAct-style RAG system for military training data/material generation, scaling to ~1000 users and cutting generation time by 50%. Also has experience designing GPU-cluster parallel computation with PyTorch and handling production incidents involving database performance and schema design.”

Ido Avnon

Screened

Junior Software Engineer specializing in AI, geospatial, and full-stack applications

Seattle, WA5y exp

“Early-stage startup engineer with experience at pre-seed and roughly Series A-stage companies, including Rage Events Inc. Shipped production full-stack features with Next.js/TypeScript, designed Postgres-backed workflow systems, and took ownership of post-launch support and fixes in fast-moving environments.”

“Built practical automation systems spanning an NLP-based news classification pipeline and a WhatsApp interaction agent. Shows strong instincts around production reliability—using structured outputs, schema validation, idempotency, retries, and clarification flows to prevent bad actions in real-world messaging workflows.”

“Entry-level candidate who built NYC Lens, a real-time Gemini-based multi-agent system that processes live camera input, identifies landmarks, and returns structured contextual insights. Despite being a fresher, they show hands-on experience with deployment on Cloud Run, modular orchestration, noisy-data handling, and reliability patterns like retries, fallbacks, and explicit state management.”

“Full-stack product engineer with hands-on ownership of a B2B e-commerce catalog at Mphasis, spanning React/TypeScript, Java/Spring Boot, and Postgres, with strong evidence of performance tuning and UX improvement. Stands out for tracing production issues across layers, leading an Angular-to-React migration, and pairing product instinct with rapid AI prototyping—placing 2nd in an advanced AI hackathon.”

“Built and owned production GenAI systems for both infrastructure automation and customer support. Most notably, they created a self-healing multi-cloud incident response system that automated 65% of tier-1 alerts and reduced application crashes by 75%, and also shipped a hybrid RAG support triage agent that automated 60% of tier-1 inquiries with human escalation guardrails.”

SaiSindhu Beeravolu

Screened

Mid AI/ML Engineer specializing in LLMs, RAG, and healthcare AI

Illinois, USA4y exp

“Healthcare ML/AI engineer with production experience at UnitedHealth Group, including an end-to-end readmission prediction system built on 50M+ patient records that improved accuracy by 18% and reduced preventable readmissions by 12%. Also shipped a clinically grounded LLM/RAG referral generator with human-in-the-loop safety controls, showing strong depth in regulated, high-stakes AI systems.”

“Backend/infrastructure-focused engineer building AI-agent products for small businesses, including a customer-service agent platform with intent routing, RAG over Pinecone, and external booking API integration. Has shipped Python/FastAPI services with JWT auth, versioned APIs, Docker deployments to AWS EC2 via GitHub Actions, and production monitoring with Prometheus/Grafana.”

“Full-stack engineer with hands-on experience building and shipping production web products across AI, frontend, backend, and DevOps. Notably built an end-to-end resume-job matching platform during an internship that processed 1000+ resumes/day and cut recruiter screening effort by 60%, and later shipped an internal operations dashboard at CHS with measurable performance gains.”

Shreyas Kumar

Screened

Entry-level AI Engineer specializing in LLMs and applied NLP systems

Syracuse, NY1y exp

“Built Lumo, a real-time voice AI companion, owning the product end-to-end across React/TypeScript, FastAPI WebSockets, and PostgreSQL. Stands out for combining deep full-stack systems thinking with voice UX polish, reliability instrumentation, and configurable parent-control guardrails in a multi-tenant setup.”

SUMANTH Metimath

Screened

Mid-level Data Scientist specializing in ML, LLMs, and AI systems

Potsdam, NY3y exp

“Candidate takes a pragmatic approach to AI-driven development, using AI as a productivity and learning aid while emphasizing personal understanding and code validation. They have hands-on experience applying AI-assisted workflows to a resume analysis and ATS scoring project, including code generation, debugging, parsing logic improvement, and testing.”

“Full-stack engineer who has owned an operations/reporting dashboard end-to-end, spanning React/TypeScript frontend architecture, ASP.NET Core APIs, and SQL data access. Stands out for combining strong UI performance optimization with pragmatic backend decisions, post-launch monitoring, and 0→1 startup platform building that improved API speed by 35% while supporting 2,000+ transactions per hour.”

Saketh Kota

Screened

Mid-level Data Scientist / ML Engineer specializing in Generative AI, RAG, and MLOps

Irving, TX4y exp

“Built and productionized a RAG-based LLM research assistant for biomedical and regulatory document search using Mixtral 7B on SageMaker, LangChain, and Milvus, cutting research time by ~40%. Has hands-on multi-cloud MLOps experience across AWS/Azure/GCP with Kubeflow/Airflow/Composer plus Terraform + ArgoCD, and applies rigorous evaluation/monitoring (latency, accuracy, hallucinations). Also partnered with a non-technical PM to deliver an insurance policy Q&A chatbot that reduced customer response time by 30%+.”