Vetted Data Structures Professionals

“Software engineer experienced delivering customer-facing, real-time industrial monitoring dashboards (motors/shafts/turbines) by partnering directly with end users to refine charts, alerts, and performance. Strong in API/platform integrations and production troubleshooting—uses feature flags, logging, validation/mapping, containerization, and performance testing to keep systems stable while iterating quickly.”

“Backend engineer who built a Node.js + SQL service integrating with the Google Ads API to periodically upload online and offline conversions via Azure Logic Apps, persisting upload records for ROI reporting. Implemented PII hashing, token validation, redundancy, and detailed failure/status logging for reliability and debuggability. Currently scoping an LLM/agent workflow (likely LangChain) to let marketing bulk-update e-commerce product data using SEO keywords without developer involvement.”

Adam Danicki

Screened

Entry-Level Software Engineer specializing in full-stack and machine learning

0y exp

“Robotics software builder who delivered an end-to-end gesture-controlled drone system using an ESP32+IMU stream and real-time ML inference mapped to Tello SDK commands. Drove reliability improvements by instrumenting the pipeline with timestamps/logging and matching training vs runtime preprocessing, reaching ~94% gesture classification accuracy; experienced with Docker/Compose for reproducible multi-service deployments.”

Michelle Gurovith

Screened

Intern Software Engineer specializing in iOS (Swift/SwiftUI) and distributed systems

Danville, CA1y exp

“Built a fault-tolerant distributed IoT sensor network on Raspberry Pi using a token-ring protocol, implementing leader election, timeout-based failure detection, and dynamic reconfiguration when nodes drop mid-round. Focused on reliability and data integrity, including exactly-once processing semantics backed by a MySQL backend and socket-level instrumentation to debug real-time coordination issues.”

“Software development intern who owned and shipped a production-used WeChat mini-program (JavaScript + MongoDB) serving ~3,000 users in a semester. Emphasizes maintainable UI architecture through modular, reusable components and clear separation between UI presentation and data/business logic, with a performance mindset (caching/reducing redundant updates).”

Sreshta Reddy Basi Reddy

Screened

Entry-level Software Engineer specializing in systems, data, and full-stack development

Hyderabad, India1y exp

“Built a production-style hackathon prototype for analyzing healthcare facility data and identifying medical deserts via natural-language queries. Stands out for a pragmatic applied-AI approach: separating retrieval from LLM reasoning, using structured JSON outputs, and designing fallbacks and data-quality checks to keep recommendations grounded and reliable.”

Jasdeep Gill

Screened

Mid-Level Software Engineer specializing in AI and web development

Abbotsford, Canada5y exp

“Built an OCR backend that trains a custom Tesseract model for proprietary fonts and scales via multi-tenant isolation (tenant-scoped APIs, per-tenant storage, JWT+RBAC). Improved high-load image processing by shifting OCR to async worker queues and adding Redis caching, cutting processing time by ~66%, and also integrated Claude API to auto-generate test cases on code changes.”

Yash Amre

Screened

Intern Data Scientist specializing in machine learning and NLP

California, USA1y exp

“Analytics-focused early-career candidate with internship experience owning reporting and system performance analysis projects end to end. They combine SQL data preparation, Python automation, and dashboard delivery with measurable impact, including roughly 50% less manual reporting and about 20% better forecast accuracy.”

“Full-stack product engineer with strong web3/blockchain experience, having built invoicing/tokenization, transaction explorer, and no-code workflow products across React, Node.js/serverless, and SQL. Stands out for combining deep technical execution with product thinking—improving onboarding completion by ~40%, shipping quickly under ambiguity, and creating reusable platform primitives for auditability and multi-tenant customization.”

“Built a production Apple-focused LLM Q&A bot that answers user issues using similar past discussion records, including large-scale scraping and cleaning of thousands of forum threads. Used BeautifulSoup + Playwright for static/dynamic extraction, PySpark + NLP for preprocessing, and LangChain RAG with a custom response-likeliness metric to evaluate performance.”

“Full-stack TypeScript/React/Next.js builder who created an end-to-end customer-facing product (AI Job Master) that generates personalized outreach from resumes and job descriptions. Demonstrates strong product + engineering ownership with rapid MVP iteration, instrumentation-driven prioritization, and pragmatic reliability patterns (microservices, queues, correlation IDs, retries) while tackling a key AI challenge: user trust and output consistency.”

“Unity gameplay engineer with AAA experience who built a highly configurable weather/day-night system (clouds/rain/sun-moon/stars) that influenced core gameplay decisions (vehicles, time-of-day, farming/animal needs). Also has hands-on multiplayer experience with Photon Fusion (including client-backend communication and physics sync troubleshooting) and has set up CI/CD and build pipelines.”

“Built and owned a Python/FastAPI backend for a custom translation service used in a showroom application, integrating DynamoDB and connecting the service to a SPA/Next.js frontend. Has exposure to Kubernetes-based deployments and GitHub Actions CI/CD, and contributed to planning an on-prem to cloud/SaaS migration at Sherwin-Williams by gathering requirements across multiple plants/factories.”

“Early-career engineer who built a self-directed production-grade security scanning/analysis pipeline that normalizes multi-scanner results, correlates CVEs, and uses an LLM to generate exploit hypotheses—then hardened it for real-world reliability (timeouts, confidence scoring, feature flags, graceful degradation). Also integrated a real-time audio ML model into Discord/Zoom and debugged intermittent latency/dropouts across Python inference, virtual audio drivers, and network jitter; experienced with IAM integrations (Entra ID/Salesforce) and cloud tooling (AWS/Docker/Kubernetes).”

“Engineer with hands-on experience building adaptive assessment and LMS-style platforms across React/TypeScript, edge/serverless backends, and Postgres, with strong evidence of cross-layer debugging and performance optimization. Also brings ML product experience from a small-team internship, where they shipped a CatBoost-powered investor demo under ambiguity and created reusable inference infrastructure.”

“Graduate-level candidate who uses AI as a disciplined engineering assistant rather than an autonomous replacement, with hands-on experience coordinating manual multi-agent coding workflows across planning, implementation, and testing. They emphasize scoped execution, clear constraints, and human ownership of final merges, suggesting a thoughtful and practical approach to AI-augmented software development.”

“Full-stack JavaScript builder who shipped a daily-blog production system end-to-end (React + Express), containerized with Docker and deployed to AWS EC2. Implemented cron-based daily workflows, WebSocket-driven real-time updates, and production-minded reliability practices like retries/backoff, idempotency via deduplication, and basic logging/monitoring.”