Vetted pandas Professionals

Harshit Vashisth

Screened

Junior AI Engineer specializing in LLMs, RAG systems, and MLOps

Remote, United States1y exp

“Robotics software engineer who built an end-to-end system ("justmatrix"), focusing on multi-agent orchestration and a multi-RAG retrieval backend/API. Has hands-on ROS experience, including a custom node for reliable high-frequency sensor data routing, plus deployment automation using Docker, Kubernetes, and CI/CD.”

Jaiden Kettleson

Screened ReferencesStrong rec.

Entry-Level Full-Stack & AI Engineer specializing in chatbots and web apps

1y exp

“Data Science honors graduate (Maryville University) who has built Python/SQL backends and a capstone website handling sensitive user data. Emphasizes secure data handling (password encryption, secure database updates) and uses Git/GitHub Pages with CI/CD-style practices for managing and deploying changes.”

Mahad Asif

Screened ReferencesModerate rec.

Mid-level Game Developer specializing in Unity, AR/VR, and cross-platform products

Rawalpindi, Pakistan4y exp

“Exceptionally young game developer who says he began at age 10 and was employed as a Unity developer at 13. He has hands-on experience building gameplay systems, VR/Web/mobile projects, Photon multiplayer features, and AI/ML experiments—including an open-source protein-model research pipeline reportedly under peer review at PLOS ONE.”

“Data engineer who has owned end-to-end ELT pipelines on Airflow + AWS (S3/Glue/Lambda) with Snowflake/Redshift, processing millions of records per day and tens of GBs via PySpark. Built strong data quality and reliability practices (40% quality improvement, 99%+ uptime), and also designed a resilient web-scraping system with anti-bot defenses and schema-change versioning plus REST APIs for serving curated data.”

“Analytics-focused candidate with experience turning messy operational and educational program data into validated reporting assets, dashboards, and AI-ready datasets. They stand out for pairing SQL/Python data preparation with rigorous validation and lightweight NLP on open-ended feedback, driving reported improvements in reporting efficiency, engagement, and student success outcomes.”

“FAU-based analytics candidate with hands-on academic project experience across SQL data preparation, Python/NLP sentiment analysis, and predictive modeling. They stand out for turning messy datasets into clean reporting tables, building reproducible analysis workflows, and translating findings into practical recommendations around operations, credit risk, and marketing ROI.”

“Full-stack engineer and Scrum Master who led a major monolith-to-microservices migration, including a micro-frontend Angular architecture using Native Federation and staged integration into the legacy app. Also built a React + TypeScript “Business Risk” product featuring a metadata-driven dynamic dashboard/forms layer backed by Spring Boot + GraphQL, with strong QA practices (unit/integration/E2E via Cypress), CI/CD, and feature toggles.”

“QA/supplier-performance focused candidate who uses defect and delivery data to spot recurring issues early, identify root causes tied to rushed timelines/high workload, and implement practical process changes (e.g., added validation steps and tightened defect definitions). Emphasizes clear, metric-backed communication to align internal stakeholders and suppliers, then monitors post-change results to confirm sustained improvement.”

Divya Patel

Screened

Mid-Level Software Engineer specializing in .NET and CMS platforms

Fremont, CA6y exp

“Built and owned end-to-end systems for the Department of Water Resources and NAHC, including a debt infrastructure management system and a TypeScript/React + .NET 6 CMS. Strong in shipping quickly with quality (CI/CD, automated testing), optimizing SQL Server performance for large datasets, and implementing microservices-style async processing with reliability patterns (retries/idempotency/monitoring). Also delivered widely adopted internal workflow automation and reporting using Power Automate and Power BI.”

“Built and deployed an LLM-powered automation pipeline that ingests voice and documents, transcribes/extracts key information into structured data, and routes it through backend workflows using Python/FastAPI. Uses n8n to orchestrate multi-step AI processes with validation, retries, and monitoring, and iterates with stakeholders via rapid demos to refine changing requirements.”

“Backend/ML engineer with deep fintech and marketplace experience: built a real-time financial analytics + algorithmic trading platform (Python/Postgres/Kafka/Redis) and drove major DB performance wins (10x faster analytics; sub-10ms response consistency). Also shipped an end-to-end ML recruitment matching platform (scraping/ETL/modeling/Django deployment) with reported 92% matching accuracy, and emphasizes production reliability via monitoring, blue-green deploys, and robust workflow error handling.”

Sarang Pratham

Screened

Junior Software Engineer specializing in data engineering and GenAI

Kundapur, India3y exp

“Built and deployed a production LLM-powered recruitment chatbot that automates key recruiting steps (sourcing, candidate engagement, screening). Strong in agent orchestration with LangGraph, including guided graph-based workflows, context-aware routing, and reliability measures like clarifying steps plus human-in-the-loop evaluation.”

“Analytics and automation candidate with experience delivering data and AI solutions for major public-sector and enterprise clients including STC, Abu Dhabi Ports, and the Ministry of Culture. They combine SQL, Python OCR pipelines, dashboards, and cloud LLMs to turn messy unstructured data into scalable workflows, with reported impact including 70% faster document processing and 80-85% reduction in manual resume screening.”

Rasheed Samady

Screened

Entry-level AI Engineer specializing in automation and ML platforms

San Francisco, CA0y exp

“Built a production Python lead intelligence pipeline that combined external APIs, website crawling, and automated opportunity brief generation, with strong emphasis on reliability, observability, and recovery. Also has hands-on Playwright experience hardening flaky, dynamic web automations and reducing intermittent failures to under 5% through logging, screenshots, session management, and retry strategies.”

“AI/ML practitioner with production experience building a RAG-powered contextual customer support agent, optimizing for low latency using vector databases and smaller LLMs. Also deployed a fraud detection model on Kubernetes with auto-scaling for heavy transactional loads, and improved chatbot accuracy by 15% through metric-driven testing and evaluation. Partners with Marketing on personalization/recommendation initiatives with measurable outcomes tied to customer feedback.”

“QA/automation tester with experience across Cypress/Playwright/Cucumber and API testing who helped a large team with limited QA bandwidth by automating a previously manual Excel verification workflow using pandas. Reported a critical data-leakage defect and found ~40 issues during an old-to-new UI migration, collaborating regularly with developers/designers to improve product quality.”

“AI engineer with hands-on experience shipping production systems across semantic search, RAG/LLM applications, and computer vision. Built a personalized e-commerce search platform with measurable relevance and latency gains, and deployed grounded GenAI chat systems that significantly reduced hallucinations while lowering support burden. Also brings edge-deployment experience in monocular depth estimation and 3D reconstruction, suggesting strong breadth across modern applied AI.”