Vetted HTML Professionals

Pre-screened and vetted.

Rishitha Madipelli - Mid-level Software Engineer specializing in cloud-native distributed systems and streaming data in Austin, TX

Mid-level Software Engineer specializing in cloud-native distributed systems and streaming data

Austin, TX7y exp
TeslaGeorge Mason University

Backend/product engineer with Tesla experience building and operating a real-time OTA update monitoring and fleet analytics platform at massive scale (telemetry from 3M+ vehicles). Delivered end-to-end systems across Kafka-based ingestion, TimescaleDB/Postgres analytics modeling, FastAPI/GraphQL APIs, and React/TypeScript dashboards, and handled production scaling incidents on AWS EKS during major rollout spikes.

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Lejia Mu - Intern Game Developer specializing in Unreal Engine 5 systems and virtual production in Shenzhen, China

Lejia Mu

Screened

Intern Game Developer specializing in Unreal Engine 5 systems and virtual production

Shenzhen, China0y exp
XiaomiNYU

UE5 gameplay animation developer focused on building and optimizing full character Animation Blueprint stacks (locomotion + jump/fall/land, montages, linked anim graphs, and layered procedural IK). Has hands-on experience debugging tricky interaction IK issues (e.g., 180-degree turn misalignment) and improving runtime performance using Unreal profiling tools and conditionalizing IK/Control Rig evaluation.

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Saiteja Gaddam - Mid-Level Data Engineer specializing in cloud data platforms and streaming analytics

Mid-Level Data Engineer specializing in cloud data platforms and streaming analytics

3y exp
IntuitUniversity at Buffalo

Data engineer (Intuit) who owned an end-to-end telemetry and subscription analytics platform processing ~22M events/day, built on Kinesis/S3/Glue/Spark/Airflow/Redshift. Strong focus on reliability and data quality (schema drift controls, quarantine layers, idempotent reruns) and performance tuning, achieving a reporting latency reduction from ~15 minutes to under 4 minutes while enabling revenue and churn analytics for business teams.

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HK

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

Boston, MA5y exp
Northeastern UniversityPenn State University

Full-stack engineer with experience spanning Amazon IMDb and Northeastern’s NeuroJSON portal, combining consumer product work with complex scientific data applications. Built IMDb’s streaming providers feature—described as the company’s most impactful feature of 2023—and has hands-on experience with React/Angular, GraphQL, AWS, Python services, and production monitoring.

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WA

Senior Ad Operations Specialist specializing in digital tagging and campaign trafficking

New York, NY10y exp
JPMorgan ChaseNYU

Ad operations-focused paid media candidate with broad exposure across major DSPs and ad servers, including DV360, AppNexus, The Trade Desk, Amazon DSP, CM360, and Sizmek. Their experience centers on campaign setup, tagging, QA, reporting, and diagnosing tracking/viewability issues rather than owning budget strategy, making them potentially strong for execution-heavy media operations roles.

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AR

Alex Ridore

Screened

Director-level Creative Technologist specializing in front-end interactive experiences

New York City Metro, USA14y exp
MullenLoweVCU Brandcenter

Design-technologist with both UX and front-end development depth, spanning high-impact brand launches and regulated pharma sales tools. Led the experience direction and technical implementation support for DuPont's Kevlar product site—featuring Three.js, AEM, and advanced motion design—which generated strong lead capture and won an Effie, and also improved Eli Lilly IVA delivery by building a grunt.js workflow that reduced update cycles from a week to just a few days.

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Shreya B - Mid-level Software Engineer specializing in backend, cloud-native, and GenAI systems in Redmond, WA

Shreya B

Screened

Mid-level Software Engineer specializing in backend, cloud-native, and GenAI systems

Redmond, WA5y exp
Quadrant TechnologiesUniversity of Cincinnati

Software engineer with strong Java/Spring Boot backend depth and hands-on full-stack experience building AI-powered enterprise knowledge assistants and customer-facing order tracking systems. Stands out for combining RAG/LLM product work, event-driven microservices, and user-trust-focused product iteration, including shipping prototypes that became the basis for broader production workflows.

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Aakash Khepar - Mid-level Full-Stack AI Engineer specializing in agentic AI systems in Tempe, AZ

Aakash Khepar

Screened

Mid-level Full-Stack AI Engineer specializing in agentic AI systems

Tempe, AZ4y exp
Arizona State UniversityArizona State University

Full-stack engineer with strong ownership across production SaaS and AI agent systems, including a multi-tenant enterprise analytics product at Fractal Analytics and an archive intelligence platform for a real nonprofit. Stands out for combining deep backend/system design, secure AI/RAG implementation, and rapid zero-to-one execution—plus multiple hackathon wins and leadership roles.

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SA

Mid-level Full-Stack Engineer specializing in AI-driven data platforms

Santa Barbara, CA5y exp
UberUniversity of Alabama at Birmingham

Full-stack engineer with 5+ years of experience who built real-time data visualization and analytics systems at Uber, spanning React/TypeScript frontends, Node/GraphQL services, Kafka pipelines, and PostgreSQL. Particularly compelling for teams needing a hands-on builder who can turn ambiguous customer needs into scalable products, and who has also applied RAG with LangChain/OpenAI over 1.8M support files to surface actionable insights.

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DC

Director-level content and AI product leader specializing in EdTech and digital content systems

Boston, MA26y exp
ZillowUniversity of Dayton

Product leader with experience at Chegg building student-focused education products, including an ebook subscription launched in response to Amazon competition that helped drive major digital growth. Also led integration of AI/ML capabilities for question classification and personalized learning workflows, with a strong emphasis on accuracy, affordability, and acting on student feedback.

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TL

Senior Full-Stack Engineer specializing in scalable web platforms

Tempe, AZ6y exp
InkSoftUniversity of Phoenix

Software engineer with 5+ years of experience building and scaling high-traffic web systems, including e-commerce-style purchasing/reservation flows and broker back-office platforms. He has hands-on experience across Next.js front ends, Python integrations, Go load-testing tools, and MySQL/Redis-backed architectures, with notable exposure to financial reporting, MT5 integrations, and commission logic.

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Melbourne Brown - Senior Software Engineer specializing in AI-driven cloud-native platforms in Atlanta, GA

Senior Software Engineer specializing in AI-driven cloud-native platforms

Atlanta, GA12y exp
McKinsey & CompanyKennesaw State University

Engineer with unusual breadth: from a tiny startup building racehorse medical-record systems on credit-card chips for live racetrack demos to modern AI-powered contract intelligence platforms in production. Brings hands-on full-stack and backend depth across React, Python, .NET, PostgreSQL, Kubernetes, and Azure, with a track record of making complex, reliability-sensitive systems work in real-world conditions.

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Weixin Feng - Junior Game Developer specializing in Unity, VR/AR, and AI-driven gameplay in Arlington, VA

Weixin Feng

Screened

Junior Game Developer specializing in Unity, VR/AR, and AI-driven gameplay

Arlington, VA3y exp
Alterstaff, Inc.Carnegie Mellon University

Unity gameplay engineer with distinctive experience building AI-native game systems, including the backend NPC interaction architecture for AI2U, a generative AI escape room game. They combine Unity/C# gameplay engineering with backend API integration, prompt-driven NPC behavior design, and production-minded resilience for latency and server issues, plus shipped Android AR work using Vuforia.

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KJ

Krishi Jain

Screened

Junior Implementation Manager / Solution Engineer specializing in AI, ERP integrations, and predictive maintenance

Chicago, IL2y exp
Continuum AIWestcliff University

LLM/agentic workflow practitioner (Continuum AI) who productionized an LLM system for manufacturing RMA intake and warranty claims by moving from a brittle prompt to a modular pipeline with RAG, function-calling extraction, deterministic validation, and strong observability. Also diagnosed and fixed an agentic ticket-triage misrouting issue by tracing failures to retrieval timeouts, adding guardrails/fallbacks, and implementing retries plus continuous evaluation—bringing misroutes near zero while creating a repeatable debugging playbook.

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RV

Rucha Visal

Screened

Mid-Level Software Development Engineer specializing in distributed systems and full-stack web apps

Seattle, USA4y exp
AmazonUniversity of North Carolina at Charlotte

Software engineer who owned customer-facing, high-traffic TypeScript/React + TypeScript backend systems end-to-end, emphasizing safe velocity through feature flags, staged rollouts, observability, and rollback-ready incremental delivery. Reports shipping more frequently with fewer production incidents and faster recovery due to these guardrails.

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SS

Mid-level Business Data Analyst specializing in Financial Services and Healthcare analytics

USA4y exp
VisaGeorge Mason University

Full-stack engineer (~4 years) who has owned and shipped customer-facing SaaS onboarding and a role-based real-time analytics dashboard using TypeScript/React with a modular backend. Experienced in microservices with RabbitMQ and strong observability practices (correlation IDs, structured logging, queue metrics), and built an internal deployment tracker integrated with CI/CD that replaced manual spreadsheet/Slack processes.

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CD

Mid-Level Software Developer specializing in Java microservices and cloud-native systems

St. Louis, MO5y exp
EpsilonSaint Louis University

Backend engineer focused on cloud/distributed systems, deploying Java 17/Spring Boot microservices on AWS EKS with RDS and Kafka. Demonstrated strong production readiness work (DB lock mitigation, Kafka idempotency, gradual rollouts) and delivered a major latency improvement (~400ms to ~100ms). Also has proven cross-layer troubleshooting skills, isolating intermittent API timeouts to a specific Kubernetes node’s network interface issue, and partners closely with ops teams to build dashboards and workflow automation (including Python scripts).

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PJ

Prachi Jain

Screened

Mid-level Machine Learning Engineer specializing in NLP, LLMs, and MLOps

Remote, US6y exp
JPMorgan ChaseUniversity of Massachusetts Amherst

Built and productionized a RAG-based analytics Q&A assistant for a financial analytics team, enabling natural-language querying across 200+ datasets (SQL tables, PDFs, compliance docs, wikis) and cutting turnaround time by 60%. Deep experience delivering regulated, audit-ready LLM systems on Azure (Azure OpenAI + LangChain) with strict grounding/citations, hybrid retrieval, and AKS-based low-latency deployment, plus strong collaboration with compliance analysts and auditors via iterative Gradio demos.

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LK

Junior Full-Stack & Data Engineer specializing in cloud platforms and cybersecurity ML

New York, NY2y exp
AccentureNYU

Built a hackathon "Patient Summary Assistant" backend focused on healthcare workflows, combining RAG-based summarization with HIPAA-minded privacy controls (NER redaction + encryption). Demonstrated strong infra skills by deploying on Kubernetes with Helm/HPA and GitOps (ArgoCD), plus migrating from OpenAI to an on-prem Llama 3 stack (vLLM, quantization, shadow-mode testing) and adding real-time Kafka ingestion for patient vitals/anomaly alerts.

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NV

Junior Data & Machine Learning Engineer specializing in MLOps and NLP

Los Angeles, United States1y exp
WorkUpUSC

ML/LLM practitioner with production experience building a healthcare review sentiment pipeline (RateMDs) using Hugging Face Transformers plus a LangChain+FAISS RAG layer for interactive querying. Also led orchestration-driven optimization of Nike’s Fusion ETL pipeline, improving runtime efficiency by 20%, and has experience translating ML outputs into Tableau dashboards for non-technical healthcare stakeholders (e.g., readmission risk).

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SR

Mid-Level Software Engineer specializing in AWS cloud services and microservices

Seattle, Washington4y exp
AmazonArizona State University

Software engineer with primary experience in Java and Python who also troubleshoots and optimizes JavaScript/React performance issues. Has handled customer-reported production problems via log-driven diagnosis and backend workflow fixes, and took ownership of simplifying and automating a service region-expansion process through time analysis and process documentation.

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NM

Nathan Moore

Screened

Principal Architect specializing in SRE, DevOps, and large-scale cloud/CDN platforms

Dallas, Texas14y exp
Inertia LabsUCLA

Engineering leader who drove the conception, PRD, architecture, and delivery of MaxCDN’s next-generation CDN platform ("E2"), including control plane work, hardware deployment planning, and observability/billing data processing. Also built Krypton Labs’ engineering team from the first hires, using a flat Agile structure and emphasizing constructive conflict, strong documentation, and remote-team accountability.

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SA

Mid-level Full-Stack Software Engineer specializing in FinTech and payments platforms

Texas, USA4y exp
PayPalNortheastern University

Worked on payments and wallet transactions, with an emphasis on observability and root-cause analysis. Delivered end-to-end A/B testing optimization and implemented Jenkins-based CI/CD automation that reduced manual implementation to 35% and cut deployments to ~2 minutes, with attention to operational considerations like on-call/call rotations.

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RC

Richard Cerow

Screened

Director of Marketing Technologies specializing in scalable web platforms for gaming

El Segundo, CA19y exp
KraftonUniversity of Notre Dame

Player-coach engineering leader focused on consumer-grade video/multimodal products and high-reliability identity/auth experiences. Led design and implementation of multi-step mobile login/MFA flows with telemetry-driven funnel improvements, shipped Node services and security fixes, and owned auth incidents end-to-end using RUM and step-level instrumentation. Introduced feature-flagged delivery and targeted review/testing practices to speed iteration ~20–30% while keeping login stability high.

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