Vetted Data Structures Professionals

Venkatasai Vorsu

Screened

Mid-level Full-Stack Software Engineer specializing in Java microservices and cloud platforms

Houston, TX5y exp

“Full-stack engineer with strong React/TypeScript and Spring Boot experience in banking and financial systems, focused on real-time transaction monitoring and payment tracking products. Stands out for scaling high-volume dashboards, solving rendering bottlenecks in live data UIs, and owning features end-to-end from frontend through APIs, Oracle data layer, cloud deployment, and production monitoring.”

“Built and shipped a real-time AI robotic inspection system, using a synthetic data generation pipeline to address rare edge cases—cutting data collection costs ~60% and boosting hard-scenario accuracy ~20%. Experienced in productionizing ML on constrained Jetson hardware and orchestrating end-to-end ML workflows with Airflow/Docker/Kubernetes, with a metrics-driven approach to reliability, evaluation, and stakeholder communication.”

“Fintech-focused mobile engineer who built and shipped a mobile wallet to both iOS and Android app stores, implementing biometric login and AI-driven KYC (face + ID verification). Demonstrates strong customer feedback loops and production problem-solving, including resolving iOS version-specific third-party AI integration issues and improving payment UX by moving from synchronous to asynchronous processing.”

“Built and shipped a production multi-agent LLM system at Solena that automated internal project intake, validation, reporting, and stakeholder communications using Python, SQL, and LangChain, with strong emphasis on reliability (structured validation, safe defaults, logging, and state tracking). Also used LangGraph to orchestrate a multi-step video summarization pipeline, and has experience partnering with non-technical stakeholders to define “completion” criteria and reporting needs.”

Annie Suzan Edwin Arokiaraj Caroline

Screened

Junior Full-Stack Software Engineer specializing in distributed systems and data pipelines

Tempe, AZ1y exp

“Backend engineer with hands-on experience building distributed data and API platforms (Kafka + Neo4j on Kubernetes), including processing 3M+ NYC taxi trip records and achieving sub-second graph analytics queries. Strong focus on reliability and performance in Python/FastAPI systems—async refactors, caching, timeouts/retries, feature-flagged rollouts, and JWT/RBAC security for production services.”

Ttanvi Tummapudi

Screened

Junior Data Scientist specializing in machine learning, predictive modeling, and applied AI research

2y exp

“Data scientist/researcher who has built two multimodal LLM systems: an AI-assisted medical triage pipeline using GPT-4o vision + RAG with confidence-scored red/yellow/green outputs, and a master’s project on multimodal cyberthreat detection combining multiple models and using TinyLlama to generate human-readable risk reports. Also partnered with business analysts at Sanvar Technologies to deliver a churn prediction pipeline and Tableau dashboard for decision-making.”

Sanskar Pandey

Screened

Junior Full-Stack Java Developer specializing in FinTech microservices

OH, USA3y exp

“Full-stack engineer with production experience building a real-time order tracking system using React + Firebase/Firestore, emphasizing audit-friendly data modeling, state-machine-based status transitions, and strong post-launch ownership (performance, security rules, reliability). Demonstrated measurable frontend performance gains by isolating real-time updates to dynamic components and applying memoization, plus backend reliability patterns (idempotency, retries) and SQL query/index optimization validated with EXPLAIN ANALYZE.”

Dalton Hutchinson

Screened

Mid-level Game Developer specializing in Unity, multiplayer, and VR experiences

Philadelphia, PA4y exp

“Unity gameplay programmer who has served as lead programmer on a small indie team, building core systems end-to-end from architecture through implementation. He combines single-player systems design, multiplayer netcode experience, cross-platform VR/mobile work, and hands-on experimentation with LLM-driven NPC gameplay prototypes.”

“Software engineer with a pragmatic, production-oriented approach to AI-driven development, using AI to accelerate coding while keeping human oversight on correctness, architecture, and final decisions. Has hands-on experience with agent-style AI workflows and has led the design and coordination of AI-agent systems with a strong emphasis on reliability, performance, and end-to-end execution.”

“Remote game QA tester with PlayStation and Xbox testing experience, using Jira to track bugs and create test case reports while collaborating directly with development teams. Has tested titles/projects including Valorant, Roblox, and Unity 3D games, and has self-studied Microsoft XR certification requirements.”

“Software engineer with experience across edtech, live gaming, and an AI document intelligence platform, delivering end-to-end customer-facing features and production backends. Built secure, automated live-session scheduling integrating Zoom and TalentLMS (JWT/RBAC, idempotency, transactions) cutting setup time from ~3 minutes to under 1 minute, and optimized real-time gaming dashboards/APIs with query tuning, caching, and CDN improvements (~60% latency reduction under peak load) on AWS.”

“Software engineer who built an AI marketing/outreach agent end-to-end: Next.js (App Router + TypeScript) frontend integrated with a Python/Django REST backend using LLMs (Gemini, ChatGPT-4o) and SQL databases. Demonstrated measurable performance wins—improved a 100k-record UI by 15% (Lighthouse) and cut a Postgres-backed search API from ~3s to ~1ms via indexing—while also owning post-launch monitoring (webhooks/cron, New Relic/CloudWatch) and customer support.”

Pranav Mishra

Screened

Junior Machine Learning Engineer specializing in LLM agents, RAG, and MLOps

Charlotte, NC2y exp

“AI/ML engineer who has shipped production systems across computer vision and conversational agents: built a YOLOv8-based wheel fitment pipeline at a Techstars-backed automotive startup, focusing on sub-second latency, monitoring, and robust fallback mechanisms that drove 2–3x page view growth and +5–6k users. Also built a voice-based interview platform orchestrating Deepgram + GPT-4 Mini + OpenAI TTS with FSM-driven reliability, and has hands-on RAG experience (LangChain, hybrid retrieval, cross-encoder reranking, custom pseudo-query generation).”

Umair Azam

Screened

Senior Full-Stack Software Engineer specializing in Ruby on Rails and React

Lahore, Pakistan10y exp

“Frontend engineer with React/TypeScript experience who has led end-to-end UI work on a fintech product (React frontend with NestJS APIs), emphasizing performance (virtualized rendering, memoization, lazy loading, profiling) and quality at scale (unit tests and TDD). Also built and iterated on a snooker sports app, simplifying UX through audience-focused design decisions and streamlined onboarding.”

Rethvick Sriram Yugendra Babu

Screened

Junior AI/ML Software Engineer specializing in Generative AI and scalable data pipelines

Tucson, AZ2y exp

“Built and operated large-scale biodiversity/ecological research platforms, integrating 50+ heterogeneous global datasets into a unified BIEN 3 schema on PostgreSQL/PostGIS and improving data consistency by 35%. Strong production engineering background (Linux monitoring, CI/CD performance gates, Docker on AWS/Azure) plus applied AI work building a Python RAG system (0.90 precision) and halving latency with Elasticsearch.”

Mayank VYAS

Screened

Mid-level AI/ML Engineer specializing in LLM agents, RAG retrieval, and IoT ML systems

Tempe, AZ4y exp

“Built production LLM-driven products including a job-hunt AI (job ranking + resume optimization) and an InterviewAI agentic pipeline using LangChain. Focused on practical deployment concerns like securing OpenAI usage via rate limiting and tiered quotas, and demonstrates an applied approach to choosing models, retrieval methods (RAG), and prompting strategies.”

Aleksander Aksionau

Screened

Senior C++/Rendering Engineer specializing in game engines and GPU (CUDA) computing

10y exp

“Gameplay/physics-focused C++/UE5 developer who builds end-to-end real-time 3D systems (custom melee hit reactions, animation, and terrain movement) and debugs deep rendering issues using GPU/pixel-shader tooling. Has hands-on experience with complex networked physics, including ragdoll replication with bandwidth compression and hybrid deterministic/non-deterministic prediction approaches, and is interested in realistic soccer/football movement systems.”

Amr Elkordy

Screened

Mid-level Sales Engineer specializing in GNSS/RTK and technical pre-sales

Santa Clara, CA3y exp

“GEODNET engineer specializing in edge-to-cloud, real-time GNSS data pipelines at global scale (thousands of heterogeneous base stations). Built deterministic-latency ingestion with RTCM/MSM normalization, jitter buffering, and firmware-aware parsing, and shipped production hotfixes using canary rollouts and deep observability. Also delivers customer-specific GNSS/RTK outputs via tested Python tooling (CLI/API) and collaborates on-site with operators to resolve firmware and network-driven issues.”

Ram Abhinav Vedant Madabushi

Screened

Junior Full-Stack/AI Engineer specializing in web platforms and LLM applications

Palo Alto, CA2y exp

“Backend engineer from FoodSupply.ai who built and evolved a scalable restaurant/supplier product and order management platform using Node.js and REST APIs. Implemented a hybrid MySQL+MongoDB data architecture, optimized performance with Redis/Prisma, and led a phased migration with feature flags and a temporary sync layer to maintain data consistency. Strong focus on production security (OAuth2, RBAC, row-level security, AWS IAM) and reliability practices (testing with Pytest, Docker/AWS pipelines).”

Adam Hinton

Screened

Mid-level Full-Stack Engineer specializing in Healthcare IT and SaaS

Philadelphia, PA3y exp

“Backend/data engineer with healthcare/medical-device experience who scaled a HIPAA-constrained local data platform to 50k users and 1B+ records, boosting processing from <500 to ~50k datapoints/sec using sharding, indexing, and SQL over Parquet (DuckDB). Strong security and reliability focus (JWT/RLS, least privilege, heavy unit/E2E testing) and a TypeScript specialist who uses type design to eliminate edge-case failures.”

“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.”

Shuchi Shah

Screened

Senior Applied AI Engineer specializing in RAG and full-stack systems

San Jose, CA13y exp

“Backend engineer with experience building an end-to-end civic tech AI platform that ingests city council meeting videos, transcribes them with Whisper, and enables natural-language Q&A via a LangChain/FAISS RAG pipeline. Demonstrated strong systems thinking by tuning retrieval for accuracy/latency/memory (cutting response time ~3s→1s and memory ~500MB→25MB) and by safely migrating an ERP from monolith toward services using dual writes, reconciliation, and idempotency to protect financial workflows.”

“Union College robotics graduate with hands-on ROS experience building an independent “waiter bot” that took spoken orders (Mozilla DeepSpeech), used OpenCV, and navigated via SLAM on a TurtleBot with LiDAR. Also led the Union College Robotics crew for four years and implemented PID control for micromouse maze robots; has additional software deployment experience with Dockerized FastAPI and CI/CD from coursework.”

“Built and deployed a "personal second brain" product (CloneMind) with an end-to-end RAG pipeline for retrieving information across PDFs, URLs, images, and audio using Next.js/Node.js/Postgres/Supabase/Redis. Demonstrates strong practical depth in retrieval quality tuning, latency reduction via caching, and stateful orchestration with LangChain/LangGraph, plus experience persuading a non-technical professor stakeholder by shipping a working prototype.”