Pre-screened and vetted in Florida.
Junior AI Engineer specializing in LLM systems and network automation
Senior AI/ML Engineer specializing in LLMs, RAG, and cloud-native MLOps
“Built and owned a real-time clinical AI assistant at Andor Health, taking it from prototype through deployment, monitoring, and iterative improvement. Brings strong healthcare-focused GenAI experience across RAG, hybrid retrieval, LoRA fine-tuning, and production Python services, with measurable gains in accuracy, speed, and reliability.”
Senior AI/ML Engineer specializing in Generative AI and conversational systems
Mid-level AI Engineer specializing in LLM agents and multimodal generative AI
Mid-level Data & AI Engineer specializing in healthcare data pipelines and MLOps
“Built and deployed a production LLM-powered clinical note summarization system used by care managers to speed review of 5–20 page unstructured medical records. Implemented safety-focused validation (prompt constraints, rule-based and section-level checks, human-in-the-loop) to reduce hallucinations while maintaining low latency and meeting privacy/regulatory constraints, integrating via APIs into existing clinical tools.”
Mid-level AI/ML Engineer specializing in Generative AI and LLM solutions
Mid-level AI/ML Engineer specializing in NLP, computer vision, and MLOps
“Analytics-focused candidate with internship and project experience at Recotap and CoUnderscore, combining SQL, Python, and BI dashboards to turn messy marketing and engagement data into decision-ready reporting. Stands out for tying analytics work to business outcomes, including ~15% CTR improvement, identifying ~40% misattributed spend, and enabling a ~$75K budget shift through better targeting.”
Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and computer vision
Mid-level AI/ML Engineer specializing in LLMs, RAG, and GenAI pipelines
Mid-level AI/ML Engineer specializing in predictive modeling, data pipelines, and RAG systems
“Built and productionized an LLM-powered internal knowledge search system in a regulated environment, using embeddings/vector DB retrieval with strict grounding and confidence gating to reduce hallucinations. Reported ~45% accuracy improvement over keyword search and implemented end-to-end orchestration, monitoring, CI/CD, and incremental re-indexing to manage latency and data freshness while driving adoption with business stakeholders.”
Mid-level Data Scientist & AI Engineer specializing in NLP, computer vision, and MLOps
Senior AI/Software Engineer specializing in cloud security and AI-powered applications