Pre-screened and vetted in the Chicago Metro.
Mid-level AI/ML Engineer specializing in GenAI, NLP, and cloud MLOps
Mid-level AI Engineer specializing in Generative AI and NLP
Mid-level Machine Learning Engineer specializing in Generative AI and MLOps
Mid-level AI/ML Engineer specializing in cloud ML, NLP/LLMs, and real-time data pipelines
Senior AI/ML Engineer specializing in MLOps and Generative AI (LLMs/RAG)
Mid-level Data Scientist/MLOps Engineer specializing in NLP, GenAI, and cloud ML platforms
“AI/ML engineer who led production deployment of a multimodal (text/video/image) RAG system on GCP using Gemini 2.5 + Vertex AI Vector Search, scaling to 10M+ documents with sub-second latency and +40% retrieval accuracy. Strong MLOps/orchestration background (Kubernetes, CI/CD, Airflow, MLflow) with proven impact on reliability (75% fewer incidents) and deployment speed (92% faster), plus experience delivering explainable ML (XGBoost + SHAP + Tableau) to non-technical retail stakeholders.”
Mid-level Software Engineer specializing in AI/ML backend systems
“AI/data engineer at ZS Associates focused on production-grade agentic systems, FastAPI microservices, and cloud-native ETL/RAG pipelines at significant scale. They’ve built multi-agent validation and diagnostic workflows inspired by their Copilot/KUBEPILOT AI work, supporting 500K+ records per day while improving ML inference performance by ~30% and cutting manual troubleshooting by 60%.”
Senior AI/ML Engineer specializing in healthcare NLP and predictive analytics
“ML/NLP engineer with healthcare and industrial IoT experience: built an Optum pipeline that converted 2M+ physician notes into structured entities and linked them with claims/pharmacy data to create an actionable patient timeline. Deep hands-on expertise in production NER, entity resolution, and hybrid search (Elasticsearch + embeddings/FAISS), plus robust data engineering practices (Airflow, Spark, data contracts, auditability) and experimentation-to-production rollout via shadow mode and feature flags.”
Mid-level AI Engineer specializing in LLM apps, RAG pipelines, and agentic workflows
Mid-level Data Scientist/MLOps Engineer specializing in NLP, GenAI, and cloud ML platforms
Mid-level AI/ML Engineer specializing in NLP, GenAI, and fraud/risk analytics
Junior AI Engineer specializing in distributed ML pipelines and time-series forecasting
Mid-level Machine Learning Engineer specializing in healthcare and enterprise analytics
Mid-level Automation & Robotics Engineer specializing in industrial controls and computer vision
“Robotics software engineer with hands-on experience building an AGV for warehouse autonomy at Kick Robotics, working across SLAM, waypoint navigation, computer vision, and ROS2/RViz simulation. Demonstrated strong on-site troubleshooting by diagnosing a real-world mapping stall via log analysis (coordinate reset bug) and deploying a fix. Also has industrial automation experience coordinating SCARA robots via EtherNet/IP and multi-robot/swarm simulations using MQTT pub-sub.”
Intern AI Engineer specializing in LLMs, NLP, and conversational search
“Student building a production trip-planning LLM agent (LangChain + Streamlit) that routes user queries across multiple tools (maps/places/Wikipedia). Implemented zero-shot multi-label intent detection with priority rules to handle multi-intent requests, and collaborates with a startup product manager to shape tone, features, and user experience.”
Mid-level AI Prompt Engineer specializing in agentic AI and automation
“Built GRETA, a full-stack multi-agent AI platform for SEO content analysis and blog-writing support, combining React/TypeScript, serverless GCP Cloud Run workflows, and LLM/tool orchestration at scale. The system reportedly reduced manual analysis by 60%, and the candidate shows strong hands-on experience shipping AI products in ambiguous environments and refining them through internal user feedback.”
Senior AI/ML Engineer specializing in Agentic AI, RAG, and LLM systems
“ML engineer with hands-on experience building production AI systems spanning agentic AI, RAG, LLM automation, fraud detection, and predictive analytics. At Origami Risk, they designed and implemented an enterprise RAG platform end to end using LangChain, LangGraph, vector search, and AWS Bedrock to improve internal knowledge retrieval, reduce manual effort, and raise response quality across teams.”
Director-level Technology Executive specializing in enterprise architecture, cloud platforms, and GenAI
Junior Machine Learning Engineer specializing in AI automation and LLM workflows
Junior AI Engineer specializing in RAG systems and full-stack development
Junior AI Engineer specializing in LLM evaluation, prompt engineering, and AI orchestration
“LLM workflow builder who has deployed a personalized GPT experience (including Delphi AI-based knowledge ingestion) and built a LangChain/LangGraph job-aggregation pipeline that ingests, normalizes/dedupes, filters, then uses an LLM to rank and summarize matches. Emphasizes production reliability with structured outputs, retries/fallbacks, metric-driven evaluation, logging/prompt versioning, and A/B testing, and collaborates with non-technical stakeholders through demo-driven iteration.”