Pre-screened and vetted.
Senior AI/ML Engineer specializing in LLMs, MLOps, and predictive analytics
“ML/AI engineer with hands-on experience building production MLOps systems for predictive maintenance and demand forecasting, including deployment, monitoring, and iterative retraining. Also shipped a RAG-based employee onboarding chatbot integrated with ServiceNow APIs and reports business impact of roughly $300k/month in reduced stockout and overstock costs.”
Mid-level Software Engineer specializing in full-stack cloud and backend systems
“Full-stack JavaScript engineer (React/Node/Vue) who has operated like a maintainer by owning an internal component library with Storybook-style examples, documentation, and non-breaking versioning. Demonstrated strong performance engineering on a source code review service—profiling bottlenecks, fixing N+1 queries, adding caching, and trimming payloads to cut latency (e.g., ~100ms to <50ms) while rolling out incremental, test-backed improvements.”
Senior AI/ML Engineer specializing in supply chain and healthcare systems
“Built and deployed AcademiQ Ai, a production LLM-based teaching assistant using GPT/BERT with RAG (LangChain + Pinecone) to handle large student notes and generate adaptive explanations/quizzes. Demonstrated measurable retrieval-quality gains (18% precision improvement, 22% less irrelevant context) by tuning similarity thresholds and chunking based on user satisfaction signals. Also orchestrated terabyte-scale, real-time demand forecasting pipelines using Airflow and Kubeflow on GCP with strong monitoring, shadow deployment, and feedback-loop practices.”
Junior ML Engineer specializing in Generative AI and cloud-based software development
“Graduate student who has built both full-stack web products and an offline Android AI assistant for visually impaired users. Particularly interesting for roles spanning product engineering and applied AI, with hands-on experience in on-device ML, privacy-sensitive deployment, and making complex AI interactions usable for non-technical users.”
Mid-level Data Scientist specializing in AI/ML, LLMs, and healthcare analytics
“Built and shipped enterprise AI products including a conversational SQL analytics platform and a production RAG system at Johnson & Johnson. Combines full-stack engineering with LLM systems expertise, and has delivered measurable impact at scale, including 48% lower retrieval latency and 37% better response relevance across 12M+ records.”
Entry-level Software Engineer specializing in full-stack and backend development
“Frontend/full-stack web developer with hands-on experience building browser-based applications including a social-style platform and a banking web app. Stands out for practical performance optimization work—separating frontend/backend architecture, designing APIs, reducing unnecessary rendering, and improving UI clarity through iterative user testing.”
“Data and backend-focused engineer with hands-on experience spanning GenAI applications, production telemetry systems, and large-scale ETL pipelines. They combine modern AI stack work (React, FastAPI, LangChain, ChromaDB) with measurable production impact, including 90% lower DB insertion latency, 50% higher ETL throughput, and 99.9% data quality in distributed environments.”
Mid-level AI/ML Engineer specializing in LLM automation and healthcare analytics
“Full-stack AI engineer who has repeatedly taken ambiguous automation and agentic products from prototype to production, including a BRD automation platform that cut manual processing by 70% and a healthcare RAG assistant with long-term memory. Stands out for combining backend/AI orchestration depth with strong product instincts around trust, observability, security, and non-technical user experience.”
Junior ML and Full-Stack Engineer specializing in AI/ML applications
“Master's-trained candidate with an AI/ML specialization who combines hands-on machine learning project work with practical AI-assisted software development. They actively use Claude, ChatGPT, and Claude Code for debugging, API integration, multi-file refactoring, and end-to-end feature scaffolding, while emphasizing validation against official docs before shipping.”
Mid-level AI/ML Engineer specializing in NLP, MLOps, and production ML systems
Junior AI/ML Engineer specializing in LLMs, RAG, and full-stack ML applications
Senior Backend Engineer specializing in cloud-native JavaScript platforms and LLM integrations
Mid-level Data Scientist specializing in LLMs, fraud detection, and healthcare analytics
Mid-level Full-Stack Python Developer specializing in LLM/GenAI for Banking & Healthcare
Mid-Level Software Engineer specializing in full-stack analytics and ML/GenAI
Principal XR & Spatial Computing Engineer specializing in enterprise AR/MR/VR training
Mid-level Software Developer specializing in FinTech and data-driven APIs
Junior NLP/ML Engineer specializing in LLM fine-tuning and long-context biomedical NLP
Senior Backend Engineer specializing in Healthcare IT and cloud microservices
Senior Software Engineer specializing in cloud-native full-stack and AI/ML systems
Junior Software Engineer specializing in backend, cloud, and data engineering
Mid-level AI/ML Engineer specializing in LLM chatbots and computer vision for medical imaging
Junior Full-Stack & ML Engineer specializing in MLOps and time-series prediction