Vetted Sentiment Analysis Professionals

Muhammad Murtaza Murtaza

Screened

Mid-level Machine Learning Engineer specializing in NLP, Computer Vision & Predictive Analytics

Islamabad, Pakistan5y exp

“Built a production LLM fine-tuning pipeline for domain-specific code generation at Pigeonbyte Technologies, including automated collection and rigorous quality filtering of 10M+ code samples (AST validation, sandbox execution/testing, deduplication, drift monitoring, and human-in-the-loop review). Also implemented end-to-end ML orchestration in Apache Airflow with data quality gates, dataset versioning in S3, benchmarking, and automated model promotion, and has a reliability-first approach to agent/workflow design.”

“Full-stack engineer with strong TypeScript/Firebase and MongoDB depth who has built research and student-scale systems end-to-end, including GCP data pipelines and Dockerized microservices. Particularly interesting for stepping beyond a frontend remit to build NLP models with NLTK that are actively used in an academic research project's Phase 2, showing initiative and real downstream impact.”

“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.”

“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.”

“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.”

“Software engineering intern with some exposure to CRM systems, outbound communication, and lead generation support. Described using web scraping, spreadsheets, and manual company research to find and qualify leads, including out-of-state prospects, though details and metrics were limited.”

“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.”

“Frontend-focused candidate with internship experience at Tetris Corporation building complex browser-based interfaces for government and public safety users. Stands out for improving performance and usability in data-heavy applications through API optimization, pagination, reusable React components, and browser-level rendering analysis.”

Nawang Yeshi

Screened

Entry-level AI workflow automation specialist

El Segundo, CA

“Recent graduate who has been independently building AI automation projects, including a Gmail/Zapier/OpenAI/Google Sheets workflow for email prioritization and an RSS-based financial news sentiment tracker. Brings a self-directed, experimentation-heavy approach to applying AI tools in real operational workflows, plus experience using YouTube analytics to refine content for specific audiences.”

“Full-stack developer who has built both operational software for universities and an AI-assisted publishing platform called HeartThreads. Notably implemented a multi-LLM fallback architecture using Ollama, OpenAI, and Claude to keep AI story-generation features available in production.”

Tanushree Kakad

Screened

Intern Software Engineer specializing in AI, computer vision, and VR

Remote0y exp

“Robotics software engineer with hands-on experience integrating vision-based perception with control logic in ROS simulation environments. Focused on debugging real-time timing/data-flow issues, improving system stability through incremental scenario testing in Gazebo, and supporting reliable deployments with Docker and basic CI/CD automation.”