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Vetted Sentiment Analysis Professionals
Pre-screened and vetted.
Siddharth Ranjan
Mid AI/ML Engineer specializing in LLMs, RAG, and cloud AI systems
“Built an AI-powered job matching platform end to end using AWS, Gemini, FastAPI, TypeScript, embeddings, and vector search. The standout result was automating manual matching workflows and scaling resume processing to roughly 2,000 resumes per minute while monitoring quality with F1 score and latency metrics.”
Sree Manasa Vuppu
Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG
“Internship at Discovery Education building a production LLM/RAG chatbot that let marketing and sales teams query and interpret Looker/BI dashboards in natural language, with responses grounded in compliance and state education standards. Emphasizes rigorous evaluation (faithfulness/precision/recall/latency) plus user-feedback analytics, and used LangChain for orchestration, chunking/context-window control, and integration with enterprise sources like SharePoint.”
Sumedha Nigudkar
Senior Digital Marketing Specialist specializing in B2B demand generation and GenAI-enabled campaigns
“Growth/partnerships marketer with experience spanning gaming/metaverse and enterprise AI GTM. Uses paid acquisition (LinkedIn/Google), network-driven distribution (joint webinars, cross-posting), and CRM dashboards to manage funnel metrics (MQL/SQL), pipeline progression, and app download impact while maintaining structured partner reporting and feedback loops.”
Rohith Reddy Aleti
Mid-level Data Scientist specializing in AI, analytics, and predictive modeling
“Data analytics and BI professional with experience turning messy institutional and customer data into decision-ready reporting and predictive systems. They combine strong SQL/Python execution with end-to-end ownership of churn analytics, stakeholder alignment, and operational rollout into dashboards and CRM workflows.”
Meghkumar Patel
Intern-level Software Engineer specializing in backend, cloud, and AI systems
“MS Software Engineering candidate at SJSU with hands-on full-stack and applied AI experience, including building DataTrust, a secure enterprise RAG assistant with ABAC-style access control, audit logging, and grounded-answer evaluation. Also built CareerPilot, an AI interview-prep product that turns LLM and speech-to-text outputs into structured, user-friendly feedback for students and job seekers.”
Hashim Kalam
Junior Software Engineer specializing in backend systems and applied AI
“Full-stack and backend-oriented engineer with experience spanning customer-facing web products, LLM-based multi-agent systems, and enterprise Go microservices. They’ve worked on a ticketing/payments platform with Stripe, an NLP-to-2D-CAD MVP, and AI orchestration using LangChain, OpenAI, and Gemini, showing a mix of product thinking, backend architecture, and applied AI experimentation.”
BHAVANA KRISHNAN
Junior AI/ML Engineer specializing in Generative AI, NLP, and MLOps
“LLM engineer who has deployed a production RAG system (LangChain/FAISS/FastAPI) for enterprise semantic search, tackling real-world latency by LoRA/PEFT fine-tuning and grounding outputs with retrieval. Brings strong MLOps (Docker, AWS EKS, CI/CD, MLflow) plus stakeholder-facing explainability experience using SHAP to align ML-driven financial guidance with non-technical domain experts.”
Srikar Tharala
Mid-level AI/ML Engineer specializing in Generative AI and RAG systems
“Currently at ProShare and reports building an AI/LLM-powered system deployed to production, aimed at helping with status-related difficulties and reducing misunderstandings across transactions. Also cites prior collaboration at Porsche with marketing teams, focusing on translating marketing goals into technical requirements and communicating solutions clearly to non-technical stakeholders.”
Ayushi Modi
Entry-level Software Engineer specializing in full-stack and AI systems
“Software engineer with hands-on experience spanning backend APIs, streaming data systems, and cloud/infrastructure automation, who is already using agentic AI workflows in a disciplined way. Stands out for combining practical systems work in Spring Boot, Kafka/Spark/ClickHouse, and Terraform/Kubernetes with a thoughtful approach to AI oversight, architecture, and multi-agent orchestration.”
Shayan Naqvi
Mid-level Full-Stack Engineer specializing in AI and geospatial SaaS
“Full-stack engineer in the renewable energy software space who has built an LLM-powered due diligence reader and self-serve geospatial upload workflows that materially reduced customer turnaround time. Combines Angular/NestJS product engineering with AI pipelines, geospatial data handling, and strong user-feedback-driven iteration, plus a side-project builder streak with a Spotify analytics app.”
kartik sharma
Mid-level Full Stack AI Engineer specializing in LLM and RAG systems
“Founding engineer and full-stack AI builder who single-handedly created Aura Groups Sweden's Trust and Growth platform across frontend, backend, ETL, and LLM services. Has hands-on experience shipping RAG-based products with OpenAI APIs and using them in real workflows, plus early-stage startup experience at nesoi.ai where they helped get an AI learning platform adopted by teams at Bain and Amazon.”
Ned Ned Zaidi
Senior Full-Stack Engineer specializing in Python, Go, and cloud-native systems
“Full-stack/backend-leaning engineer with hands-on experience spanning Python, Go, React, Kafka, PostgreSQL, Redis, Docker, and Kubernetes. They stand out for building real-time analytics and decisioning systems, plus a healthcare-focused B2B SaaS compliance/data integration platform that combined high-throughput event processing, dashboarding, and third-party integrations in a startup-style, high-ambiguity environment.”
Manisha Manjunatha
Mid-level Backend Software Engineer specializing in Java/Spring Boot and AWS microservices
“Owned and stabilized Decathlon e-commerce payment services, taking a prototype reliability effort to production by implementing failure detection/retries, load testing, and DB performance optimizations—reducing payment failures and cart abandonment. Also demonstrates an LLM/agentic workflow support mindset with strong observability, rapid incident diagnosis, and durable prevention via RCA, safeguards, and regression/replay testing, plus experience supporting sales/support with technical reassurance.”
Nischit Patel
Mid-level Software Development Engineer specializing in Python, APIs, and AWS
“Backend engineer with experience modernizing legacy systems and building modular Python/Flask services, including a REST-to-GraphQL migration for an e-commerce platform that improved API response time by 45%. Strong in performance and scalability work across PostgreSQL/SQLAlchemy (indexing, JSONB, N+1 fixes, connection pooling) and high-throughput systems (Celery + Redis), plus integrating ML microservices with TorchServe, Kafka streaming, feature stores, and Prometheus/Grafana monitoring.”
Srihari Kamath
Junior Data Analyst specializing in analytics, BI, and machine learning
“Analytics professional with experience spanning infrastructure, energy, and digital engagement data. They have built SQL and Python workflows to turn messy operational data into trusted reporting assets, and led a wind turbine SCADA analysis that quantified roughly $1M in cumulative performance loss and translated findings into actionable Power BI dashboards.”
Sam Sharif
Senior AI Engineer specializing in machine learning, GenAI, and MLOps
“Built an end-to-end agentic population health strategy copilot for healthcare leadership, turning broad chronic disease questions into structured, evidence-backed strategy briefs. Stands out for combining healthcare domain knowledge with production-grade GenAI implementation, including LangGraph orchestration, Databricks/MLflow deployment, human review, and quality gates focused on citations, metrics, risks, and safety.”
SaiLokesh Gayam
Mid-level Full-Stack Software Engineer specializing in AI and RAG systems
“Backend/AI engineer who built an enterprise RAG chatbot over 40,000+ technical documents, owning the system from ingestion and retrieval design through launch, optimization, and incident prevention. Stands out for treating LLM reliability as a data, retrieval, and observability problem—delivering 90%+ benchmark accuracy, ~50% fewer hallucinations, and major gains in lookup speed and latency.”
Ganavi Hemachandra
Mid-Level Software Engineer specializing in backend microservices, payments, and ML pipelines
“Backend engineer who has led redesigns and migrations for a real-time logistics platform, improving scalability and resilience while managing eventual consistency tradeoffs. Demonstrates strong distributed-systems rigor (idempotency, transactions, async queues, monitoring) and builds secure, versioned FastAPI APIs with JWT/OAuth2, RBAC, and database row-level security.”
“Built a production AI-powered university marking system that automates question generation and grading from PDF course materials using a RAG pipeline (S3 + Pinecone) orchestrated with LangChain/LangGraph and deployed on AWS ECS via Docker/ECR and GitHub Actions CI/CD. Addressed a key real-world LLM challenge—grading consistency—by implementing rubric-based scoring, retrieval re-ranking, and standardized context summarization, validated against human instructors.”
HarshaVardhanRao Vemuganti
Junior AI/ML Engineer specializing in Generative and Agentic AI
“Built and deployed a production-grade LLM agent for credit management and accounts receivable automation, integrating ERP/MySQL data via a RAG pipeline and exposing services through FastAPI with Pydantic-validated outputs on AWS Bedrock. Emphasizes reliability and compliance for financial operations using schema validation and human-in-the-loop review, reporting ~32% reduction in manual work and ~41% improvement in response time/reliability.”
Tharun Chowdary Malepati
Mid-level AI/ML Engineer specializing in GenAI, NLP, and production MLOps
“AI/LLM engineer who built and deployed a production healthcare RAG chatbot ("DoctorBot") with strict medical safety guardrails, an 85% confidence-gated verification layer, and latency optimizations that cut responses from ~8s to ~2–3s. Also worked on finflow.ai to generate finance/banking test cases from BRDs, collaborating closely with non-technical domain stakeholders, and has hands-on orchestration experience with LangChain/LangGraph and agentic evaluation/monitoring practices.”
Eltayeb Yousif
Entry-level sales and growth professional specializing in Web3 and data-driven marketing
“Outbound-focused sales candidate from Ridgeway with a strong founding-SDR mindset, generating 15-25 meetings and 8-12 SQL-level opportunities per month while influencing $40k-$80k in monthly pipeline. Stands out for building structured, research-driven outbound systems and using personalized, multithreaded outreach tied to real business triggers like product launches and growth hiring.”
Alejandro Santillanes
Entry-level NLP and machine learning student specializing in computational linguistics
“Early-career candidate with academic data science and machine learning project experience, including a YouTube comment sentiment analysis project comparing LSTM and GRU models. Demonstrates a collaborative working style, structured task planning, and careful review of final deliverables in team-based project settings.”
Aishwarya Yogananda
Entry-level Machine Learning Software Engineer specializing in backend AI systems
“Built an AI GTM Copilot that consolidated 5+ sales tools into a single browser-based workflow for sales teams, combining LLMs, data enrichment, and outreach automation. Brings a rare blend of ML, backend, and front-end experience, with concrete wins in performance optimization, workflow design, and measurable UX improvements.”