Pre-screened and vetted.
Entry-level Full-Stack Engineer specializing in AI SaaS and web platforms
Mid-level Full-Stack Engineer specializing in AI-driven distributed systems
Mid-level Full-Stack Engineer specializing in cloud-native microservices and GenAI
Mid-level Backend Software Engineer specializing in AWS serverless and distributed systems
Mid-Level Full-Stack Software Engineer specializing in Java/Spring and AWS serverless
Mid-Level Full-Stack Software Engineer specializing in backend systems and event-driven architecture
Junior Software Engineer specializing in backend AI systems
Mid-level Full-Stack Software Engineer specializing in web platforms and AI
Junior Software Engineer specializing in full-stack, mobile, and cloud systems
Senior Software Engineer specializing in AI/ML and cloud backend systems
Mid-level Java Software Engineer specializing in backend systems and AI-integrated platforms
Senior Backend Engineer specializing in cloud-native microservices and AI integrations
Mid-level Full-Stack Engineer specializing in SaaS, HR Tech, and distributed backend systems
Junior Computer Science student specializing in robotics, ML, and quantum computing research
“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.”
Mid-Level Full-Stack Software Engineer specializing in web platforms, cloud, and test automation
“Full-stack engineer with hands-on ownership of production systems, including a Kafka-based notification/alerting platform (Node.js + React) deployed on AWS with Docker/GitHub Actions, achieving ~95% email delivery reliability. Demonstrates strong operational maturity (observability, CI/CD, zero-downtime migrations) and experience shipping in ambiguous environments (SJSU project) with evolving requirements.”
Entry-level Machine Learning Engineer specializing in computer vision and systems
“ML-focused builder who has shipped an end-to-end income-class prediction product: built the data pipeline, trained models, deployed via Streamlit with a live UI, and tracked success via accuracy (84%), adoption, and latency. Demonstrates strong practical MLOps instincts (Docker/Streamlit Cloud, logging/monitoring, caching) and data engineering reliability patterns (schema checks, idempotency, retries, backfills) while iterating quickly in ambiguous, solo-project environments.”
Mid-level Data Engineer specializing in ETL pipelines on GCP
“Full-stack engineer from Larix Technologies who led a Next.js migration feature: an internal real-time workflow status dashboard built with App Router/TypeScript using server components for initial render and client polling for live updates. Demonstrates strong post-launch ownership—monitoring latency/error rates, adding caching and payload reductions, and optimizing Postgres queries/indexes—plus experience building durable RabbitMQ-based message routing workflows with idempotency, retries, and dead-letter queues.”
Junior Full-Stack Software Engineer specializing in AI-powered SaaS
“Full-stack engineer from an early-stage AI SaaS startup who owned and shipped a production AI-powered PDF document chat and sharing feature end-to-end (React/TS + Node + Postgres on AWS). Demonstrates strong product thinking through layered success metrics and tight feedback loops, plus hands-on reliability/observability work (CloudWatch, structured logging, alarms) and robust ingestion pipeline patterns (idempotency, retries, reconciliation).”