Vetted Celery Professionals

“Built and shipped a production LLM hallucination detection and monitoring pipeline using semantic-level entropy (embedding-clustered multi-generation variance) to flag unreliable outputs in downstream automation. Implemented a scalable async architecture (FastAPI + Docker + Redis/Celery) with strong observability (structured logs + PostgreSQL) and developed evaluation loops combining controlled prompts and human review; also partnered with non-technical stakeholders on AI-driven form validation/document processing.”

“Hands-on engineer who has taken an LSTM Bitcoin forecasting model from notebook to a production-grade, monitored API (Docker/Gunicorn/Nginx, Prometheus/Grafana, blue-green rollback) delivering 99.9% availability and ~110–120ms p95 latency. Also built an RFID self-checkout prototype spanning Raspberry Pi + firmware + networking, using deep instrumentation to eliminate double-charges/timeouts (<0.1%) and reduce checkout time ~20% through idempotency, debounce logic, and hardware fixes.”

Yash Mahajan

Screened

Junior Software Engineer specializing in AI, full-stack development, and applied ML

Fullerton, CA2y exp

“AI/full-stack product builder who has shipped production agentic systems in both customer support analytics and medical claims automation. They combine React/Next.js frontends with Python-based async backends and LLM orchestration, delivering measurable outcomes like 60% cost savings, 40% less manual review, and reducing claims processing from 30 minutes to 20 seconds.”

Hamna Anwar

Screened

Senior Full-Stack Engineer specializing in Go backend systems

Hayward, CA8y exp

“Full-stack/backend engineer with startup-style experience spanning healthcare and B2B infrastructure SaaS. Has worked across Python, Go, and React/TypeScript, including migrating services from Node.js to Go, building microservices and dashboards, and delivering measurable API performance gains through database tuning and Redis caching.”

“IBM Power/AIX engineer who has owned a large production estate (20+ Power9/Power10 frames and 400+ LPARs) with vHMC and dual-VIOS HA. Has hands-on incident recovery experience (NPIV/RMC issues, LPM restores) and PowerHA failovers, plus modern DevOps exposure using Terraform on AWS and CI/CD with GitHub Actions/Jenkins (including deploying AI/RAG and vision workloads).”

“Software engineer building AI-powered automation features in commercial real estate, including brochure generation and property listing workflows. They combine FastAPI/Redis/Celery backend architecture with multi-agent LLM design, structured prompting, testing, and production monitoring, and are now actively learning RAG and vector databases to make outputs more personalized.”

“ML/NLP engineer who has built production systems end-to-end: a real-time recommendation platform (100k+ profiles) using BERTopic-style clustering and a RAG-based news summarization/recommendation stack with ChromaDB. Strong focus on scaling and reliability (GPU batching, Redis caching, Kafka ingestion, Docker/Kubernetes, Prometheus/Grafana) and on maintaining model quality over time via drift monitoring and retraining triggers.”

Dhairya Gajjar

Screened

Mid-Level Software Engineer specializing in Healthcare Data Platforms

Remote2y exp

“Backend/ML engineer with healthcare domain experience building secure Medicare/Medicaid data APIs and real-time patient risk scoring. Shipped an end-to-end ML pipeline (scikit-learn/XGBoost) served via SageMaker and integrated into Flask APIs, with strong production reliability practices (Kafka schema validation, regression replay, observability, drift monitoring, and human-in-the-loop guardrails).”

Ahmad Rayyan

Screened

Entry-level Full-Stack Engineer specializing in Applied AI and multi-agent systems

Pakistan1y exp

“Built both traditional full-stack products and advanced LLM systems, from a React/Flask dashboard used by instructors to monitor GitHub contribution patterns to multi-agent benchmark infrastructure at Analytiverse. Particularly strong in evaluation-heavy AI engineering: designed executable verifiers, force-zero anti-reward-hacking checks, and token-optimization strategies that delivered a 40-point pass-rate lift and 90x token reduction on SwarnBench tasks.”

“Python backend developer from Larix Technologies who built and scaled microservice APIs for an omnichannel messaging SaaS (WhatsApp/Instagram/Facebook) and led production performance fixes during peak traffic, cutting webhook latency ~50%. Also shipped applied AI products end-to-end: a RAG-based PDF assistant (LangChain + Mixtral via Groq + React) and a BI agent that plans/executes/verifies multi-step analytics with strong guardrails and auditability.”

“Full-stack product engineer who has built both a production-grade React/Next.js analytics platform and a Stripe-based subscription system end to end, with measurable business impact including churn reduction, reporting automation, and cost savings. Also stands out for 0-to-1 work in the digital art space, where they built an AI-powered cataloguing and delivery pipeline over 30TB of assets using computer vision, Shopify, and cloud infrastructure.”

“Engineer with growth-stage startup experience on a 6-7 person cross-functional team, working across backend, data, and frontend systems. They’ve driven concrete improvements to high-volume data ingestion pipelines through batch processing and database optimization, and have built B2B SaaS data platforms for enterprise customers with multi-tenant support, integrations, and scalable backend services in Python and Go.”