Pre-screened and vetted in North Carolina.
Mid-level Machine Learning Engineer specializing in MLOps and scalable ML pipelines
Junior AI/ML Engineer specializing in LLM agents, explainable AI, and computer vision
“Robotics/computer-vision engineer with industrial safety monitoring experience, building real-time pose estimation (TRTPose) and 2D-to-3D localization and optimizing pipelines to sustain 30+ FPS under heavy multi-entity load. Also brings edge-to-cloud distributed systems work (HoloLens + Google Vision/Translation) and production ML deployment experience using Docker/CI/CD across finance and edge camera environments.”
Junior AI Engineer specializing in LLM pipelines, RAG, and computer vision
“Built and deployed an on-prem, HIPAA-compliant LLM pipeline for oncology-focused clinical note generation and decision support, emphasizing grounded differential diagnosis and explainable reasoning via RAG to reduce hallucinations. Also created a LangGraph-based multi-agent academic paper search system integrating Tavily, arXiv, and Semantic Scholar with an orchestrator that routes tasks to specialized sub-agents.”
Mid-level AI/ML Engineer specializing in GenAI, RAG, and cloud-native ML platforms
Senior Machine Learning Engineer specializing in NLP, Generative AI, and healthcare/legal AI
Mid-level Machine Learning Engineer specializing in fraud detection and LLM applications
“Unreal Engine UI engineer focused on scalable, production-ready UI architecture (C++/Slate/UMG/CommonUI) with strong designer enablement via decoupled, interface-driven patterns and MVVM. Demonstrated measurable performance wins: replaced 200+ per-frame Blueprint bindings to cut UI prepass/paint from 4.2ms to 0.5ms and reduced VRAM by ~120MB using texture streaming proxies.”
Senior Machine Learning Engineer specializing in Generative AI, NLP, and MLOps
Mid-level Software Engineer specializing in AI-driven backend and full-stack FinTech systems
Mid-level Software & ML Engineer specializing in cloud data platforms and MLOps
Mid-level AI/ML Engineer specializing in LLM, RAG/GraphRAG, and fraud analytics
“LLM/agent engineer who has deployed a production internal assistant to reduce employee inquiry resolution time while maintaining regulatory compliance. Experienced with RAG, hallucination risk triage, and graph-based orchestration (LangGraph) for enterprise/banking-style workflows, emphasizing schema-validated, citation-backed, tool-constrained agent designs and tight collaboration with non-technical business/compliance stakeholders.”
Mid-level AI/ML Engineer specializing in LLMs, RAG systems, and MLOps
Mid-level AI/ML Engineer specializing in fraud detection, risk modeling, and LLM/RAG systems
Senior Full-Stack Java Engineer specializing in AI/LLM automation and regulated systems
Mid-level AI/ML Engineer specializing in production ML, NLP/LLMs, and risk & automotive analytics
Mid-level Full-Stack Software Engineer specializing in AI platforms and microservices
“Backend engineer currently building an AWS Lambda/FastAPI inventory recommendation system using a LangChain + GPT-4 RAG pipeline and MongoDB vector search; drove major cost optimization via Redis caching (60% reduction) while sustaining 10k+ daily requests under 2s latency. Previously deployed Node.js microservices on AWS OpenShift with Jenkins/Helm at UnitedHealth Group and led a zero-downtime monolith-to-microservices migration at Verizon, including RabbitMQ-based real-time messaging with DLQs and idempotency.”
Senior AI Engineer specializing in Agentic AI and distributed systems
“LLM/agentic workflow engineer with healthcare domain experience who built a HIPAA-compliant multi-agent RAG system for clinical review automation at UnitedHealth Group, achieving 92% precision and cutting latency 40% through async orchestration and Redis semantic caching. Also has strong data engineering orchestration background (Airflow on AWS EMR with Great Expectations) and a proven clinician-in-the-loop feedback process that improved model faithfulness by 18%.”
Mid-level Generative AI Engineer specializing in LLMs and RAG
Mid-level Robotics & Computer Vision Engineer specializing in perception and industrial automation
“Robotics software/vision engineer with hands-on experience building motion-tracking systems that fuse camera-based 3D tracking with IMU orientation to reproduce tool motion for automated spray painting. Has implemented ROS nodes/packages for Orbbec camera streaming and SAM3-based segmentation, plus CAN bus coordination between robots and Dockerized deployment for a pick-and-place robotic cell.”
Mid-level Applied AI Engineer specializing in agentic LLM workflows
“AI engineer with production experience building a LangGraph-based, stateful multi-agent system at MetLife to automate complex insurance claims adjudication, integrating document discovery, Azure Document Intelligence OCR/extraction, and health data analysis. Strong in agent orchestration and production deployment (Docker + FastAPI REST APIs), with a structured approach to reliability, evaluation, and stakeholder-driven requirements.”
Intern AI Engineer specializing in LLMs, RAG, and multimodal generative AI
Mid-level AI Engineer specializing in Generative AI, RAG, and agentic workflows
Senior Machine Learning Engineer specializing in Search, Recommendations, NLP and RAG