Pre-screened and vetted.
Senior Growth & Brand Marketing Leader specializing in performance-driven storytelling
Entry-Level Software Engineer specializing in AI/NLP and full-stack development
Intern Software Engineer specializing in AI, cloud, and backend systems
“Candidate has internship and graduate-project experience building AI agents, including a production log-analysis assistant using a lightweight agentic/RAG-style workflow with local GPT training and validation against historical logs. They also worked on Android/iOS game build and release processes in a Unity-based robot racing game environment, and highlight measurable LLM outcomes including 80% analysis accuracy, 2-5 second latency, and 50% cost reduction.”
Junior Software Engineer specializing in AI, voice, and full-stack product engineering
“Product-minded full-stack engineer from SuperU who built AI voice-agent infrastructure end-to-end, from React/TypeScript campaign UIs to a forked n8n orchestration backend and Postgres multi-tenant data model. Stands out for shipping quickly in ambiguous startup environments, debugging deep reliability issues across layers, and delivering measurable gains like activation rising from 20% to 70%+ and call drops falling below 0.5%.”
Entry-Level Software Engineer specializing in AI, systems programming, and full-stack development
“Systems-focused C++ engineer who built a 32-bit CPU simulator end-to-end (custom ISA, full memory model, fetch-decode-execute loop) and solved tricky recursion/stack-frame correctness issues through heavy instrumentation and tracing. Has strong Linux and user-kernel boundary experience (procfs) plus modern build/test tooling (Docker, CI/CD, pytest), and is confident ramping quickly into ROS/ROS2 despite not having used it directly.”
Entry-level Full-Stack Software Engineer specializing in .NET, React, and cloud systems
“Full-stack developer with .NET and cloud-based development experience who has built a practical AI-assisted engineering workflow using Copilot, Claude, and GPT across coding, debugging, testing, and review. Stands out for using AI to accelerate delivery while still applying careful validation and human judgment for high-impact performance and security decisions.”
Entry-level Data Analyst and AI Engineer specializing in machine learning and LLM systems
“Founding-engineer-oriented full-stack product engineer who built an AI tutor system end-to-end, spanning React UI, FastAPI backend, retrieval/LLM pipelines, and Postgres optimization. Stands out for combining product thinking with deep systems work: improving onboarding and activation, shipping quickly with beta users, and abstracting reusable retrieval infrastructure for multiple use cases.”
Senior Backend Engineer specializing in AI automation and scalable API systems
Mid-level AI/ML Engineer specializing in LLM agents, RAG pipelines, and AI automation
Mid-level Software Engineer specializing in Generative AI and cloud-native microservices
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic systems
Mid-level AI/ML Engineer specializing in GenAI, agentic AI, and RAG pipelines
Mid-level AI/ML Engineer specializing in NLP, GenAI, and conversational AI
“Built and deployed a production bilingual (Bengali/English) AI virtual assistant that replaced IVR for telecom customer service at massive scale (~15M users), integrating ASR/TTS, Rasa dialogue management, and custom NLP. Overcame low-resource Bengali data and noisy call-center audio with synthetic data augmentation and transformer fine-tuning, achieving significant production gains including ~50% reduction in support calls.”
Junior Full-Stack Software Developer specializing in cloud-native apps and data/AI
Mid-Level Backend Software Engineer specializing in scalable APIs and cloud deployments
Junior Machine Learning Engineer specializing in LLMs, RAG, and fine-tuning
Mid-level AI/ML Engineer specializing in LLMs and RAG systems
Junior AI/ML Engineer specializing in LLM systems and personalization
“Backend engineer who built and scaled AmazonProAI, a multi-tenant SaaS platform for Amazon sellers, using a modular Django/DRF monolith with strict seller-level isolation and security controls. Led a controlled SQLite-to-PostgreSQL migration and hardened bulk Excel ingestion with idempotency and data integrity constraints to prevent duplicate metrics and noisy alerts while keeping the system ready for future service extraction.”