Vetted Operating Systems Professionals

“New grad candidate with graduate research experience building a multi-agent RAG pipeline from scratch, including worker-coach orchestration and an evaluation framework. Most notably, they improved structural similarity from 67% to 98% by designing validation and retry logic to reduce hallucinations, showing strong practical depth in agentic AI systems.”

“AI engineer focused on production-grade LLM systems rather than prompt-only solutions, with hands-on experience building citation-grounded RAG products and multi-agent workflows. Most notably built a financial document intelligence system for SEC filings and contracts that achieved ~92% recall@5, cut latency below 2 seconds, reduced hallucinations, and turned analyst research from hours into seconds.”

“Full-stack software engineer who shipped production systems in academic and e-commerce contexts, including a UC Irvine course recommendation platform with async Kafka-based OCR processing (Tesseract) and LangChain-driven recommendations. Strong in building polished React/TypeScript dashboards (Figma-to-implementation) and owning Python backends (FastAPI/Flask) with solid API design, caching, and AWS EKS deployments; delivered measurable impact (tripled engagement, ~50% faster processing).”

“Research assistant who single-handedly built and integrated an indoor autonomous wheelchair system using NVIDIA Jetson Nano, LiDAR, and a stereo camera. Implemented a multi-sensor perception pipeline (OpenCV/PCL) with ROS-based modular nodes, TF frame management, and robust debugging via RViz/rosbag, plus simulation testing in Gazebo and Dockerized environments for portability.”

Raunak Bandyopadhyay

Screened

Intern-level Full-Stack Engineer specializing in AI and web systems

Amherst, MA0y exp

“Backend-focused intern in telehealth who combined engineering, QA leadership, and emergency infrastructure ownership. Built a text chat feature and an OpenAI-powered therapy chatbot, then stepped up to rebuild AWS infrastructure after it was accidentally deleted, while also improving chat responsiveness and reporting a 30% engagement lift.”

keerthana bhukya

Screened

Junior Software Engineer specializing in AI/ML and cybersecurity

Stockton, CA2y exp

“Salesforce-focused engineer with hands-on depth across Sales Cloud, Service Cloud, Apex, LWC, and Aura. Stands out for owning end-to-end automation features, making thoughtful async architecture decisions to balance performance and reliability, and designing responsive Lightning interfaces that hold up under large data volumes.”

Garv Goyal

Screened

Intern software engineer specializing in AI systems and full-stack development

Vienna, VA1y exp

“Full-stack/product-minded engineer with a strong infrastructure foundation who has built both cloud automation systems and an AI voice interview coach. Stands out for combining hands-on coding with pragmatic product thinking: they improved user trust through scorecard redesign, built resilient speech handling around flaky browser APIs, and delivered measurable backend performance gains during startup internships.”

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.”

Mohammed Mudassir Hussain Shaikh

Screened

Entry-Level Full-Stack Software Engineer specializing in serverless AWS and AI applications

Tempe, AZ1y exp

“Built and deployed serverless AWS applications (Lambda/S3/RDS Proxy) including a NASA L’Space React + Python data analysis tool, focusing on performance for large datasets. Demonstrates strong cloud troubleshooting across compute and networking (CloudWatch-driven diagnosis, EC2 scaling, security group fixes) and a user-driven iteration loop that improved product usability with dynamic filtering and interactive UI.”

Ronit Shetty

Screened

Entry-level Robotics Engineer specializing in SLAM, sensor fusion, and embedded avionics

Boston, MA1y exp

“Robotics software engineer focused on perception/SLAM and systems integration, recently built a quasi-dynamic mapping pipeline to track and reconstruct articulated objects (e.g., drawers) from RGB video using SAM2, COLMAP SfM, and 3D Gaussian Splatting. Also has strong ROS2 sensor-pipeline experience (custom messages, MCAP rosbag deserialization, tf2) and demonstrated real-time performance tuning by accelerating an ICP-based LiDAR SLAM component ~30x (from ~3s to <100ms per frame).”

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.”

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.”

“Front-end/full-stack engineer with about two years of experience building high-stakes internal trading operations tools for traders and operations engineers. Stands out for combining deep browser performance work, strong TypeScript/React architecture, and direct user observation to improve incident response workflows in live production environments.”

“Full-stack engineer who has built merchant marketing products end to end, including a unified campaign management system and an AI-assisted campaign generation pipeline using GPT-4-class models and LangGraph. Stands out for combining TypeScript-heavy product engineering with practical LLM architecture, evaluation, and guardrail design in production, plus experience operating in ambiguous early-stage environments.”

“Backend/data engineer with hands-on production experience building a real-time notification API on Flask/Celery/Postgres and scaling it on AWS with Docker, Redis queuing, and SQLAlchemy query optimization. Also delivered AWS serverless deployments (Lambda) using Terraform + GitHub Actions and built AWS Glue ETL pipelines from S3 to Redshift with CloudWatch monitoring and DataBrew data quality checks.”

“Backend/full-stack engineer with experience spanning AI-powered fintech features and high-volume roadway surveillance/ALPR platforms. They have owned production APIs, improved API latency by 35% through database/query optimization, and helped drive a Kafka-based ingestion architecture that increased throughput by 30% while improving reliability at scale.”

“Built SparkyAI, a gamified college-essay writing assistant (hackathon project at ASU in 2025) using React/styled-components, Firebase (OAuth/DB), and OpenAI APIs, with concrete scalability and performance measures like rate limiting, indexed queries, code splitting, and conversation caching. Also designed a global low-latency voice-to-LLM architecture leveraging WebRTC, regional containerized services, global load balancing, streaming STT/TTS, and end-to-end encryption with minimal logging.”

“Healthcare-focused ML/LLM engineer who built a production hybrid RAG workflow to automate prior authorization by retrieving from medical guidelines/historical cases (FAISS) and generating grounded rationales for clinicians. Strong in operationalizing ML with Airflow/Kubeflow/MLflow on SageMaker, optimizing latency (ONNX/quantization/async), and reducing hallucinations via evidence-only prompting; also partnered closely with clinical ops to deploy a readmission prediction tool used in daily rounds.”

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.”

“Builder of practical AI-backed products across developer tooling, travel search, defense, and healthcare-style workflows. They shipped an MCP/FastAPI/Gemma context-compaction system that cut token usage by about 80%, built a flight-price AI layer that validates LLM output against live search data, and helped shape a visionOS command center for a military air wing.”

“Full-stack product engineer at AllCheer who has shipped production AI workflow systems in a compliance-sensitive healthcare operations context. They built React/FastAPI products with LangChain and OpenAI to automate release-of-information and note-extraction workflows, delivering measurable impact including ~60% faster processing, ~$20K annual savings, and ~92% extraction accuracy.”

“Frontend engineer with hands-on experience building a real-time financial market dashboard at FinSight AI, handling 30+ live data streams with React, TypeScript, WebSockets, and performance-focused rendering patterns. Stands out for measurable production impact, including a 70% reduction in unnecessary re-renders, plus strong real-time visualization and UX optimization experience.”

“Backend/data engineer with hands-on production experience across Azure and AWS: built FastAPI + PostgreSQL services with Azure AD OAuth2/JWT auth and strong reliability patterns (timeouts, retries, correlation IDs). Delivered AWS Lambda/ECS solutions with Terraform/CI-CD and cost controls (SQS buffering, reserved concurrency), and built/operated AWS Glue ETL pipelines into Redshift while modernizing legacy SAS reporting into Python microservices with parity testing.”