Pre-screened and vetted.
Junior Machine Learning Engineer specializing in predictive modeling and GenAI RAG systems
“LLM engineer who built and deployed an emotionally intelligent AAC communication system using an emotion-aware RAG pipeline (Empathetic Dialogues + GoEmotions) and a PEFT-adapted model. Experienced with LangChain/LangGraph and custom Python orchestration, focusing on reliability (guards, schema validation, fallbacks), latency optimization, and rigorous evaluation (automatic metrics + human-in-the-loop), with a reported 18% user satisfaction improvement.”
Mid-level AI/ML Engineer specializing in production ML, MLOps, and NLP
“Built and deployed a transformer-based clinical document classification system that processes unstructured clinical notes in a HIPAA-compliant healthcare setting, served via FastAPI on AWS and integrated into an Airflow/S3 pipeline. Demonstrates strong end-to-end MLOps skills (data quality remediation, low-latency inference optimization, monitoring with MLflow/CloudWatch) and effective collaboration with clinicians to drive adoption.”
Junior Machine Learning Engineer specializing in multimodal systems and LLMs
“Built and productionized a domain-specific LLM-powered RAG knowledge assistant at JerseyStem for answering questions over large internal document corpora, owning the full stack from FAISS retrieval and LoRA/QLoRA fine-tuning to AWS autoscaling GPU deployment. Drove measurable gains (28% accuracy lift, 25% latency reduction) and improved reliability through hybrid retrieval, grounded decoding, preference-model reranking, and Airflow-orchestrated pipelines (35% faster runtime), while partnering closely with non-technical stakeholders to define success metrics and ensure adoption.”
Junior Machine Learning Engineer specializing in LLM fine-tuning and semantic retrieval
“Backend engineer with legal-tech and AI workflow experience: built JurisAI, an end-to-end legal research system using OCR + embeddings + Pinecone vector search to deliver citation-grounded LLM answers with safe failure modes (~90% recall@K). Also led a GW Law metadata migration into Caspio with batch validation and parallel rollout, and has strong FastAPI/GCP production reliability and observability practices.”
Mid-level Software Engineer specializing in AI/ML and Data Engineering
Junior AI Engineer specializing in LLM agents and computer vision
Senior Data Engineer specializing in cloud lakehouse and AI/ML pipelines
Director-level Cloud & DevOps leader specializing in AWS infrastructure and security
Mid-Level Machine Learning & Backend Engineer specializing in computer vision and robotics systems
Mid-level Machine Learning Engineer specializing in production ML, MLOps, and LLM retrieval systems
Mid-Level Full-Stack Software Engineer specializing in AI-powered web applications
Mid-level Software Engineer specializing in Python backend and full-stack web systems
Mid-level Machine Learning Engineer specializing in NLP, MLOps, and predictive risk modeling
Junior AI/ML & Full-Stack Software Engineer specializing in LLM agents and RAG
Mid-level Prompt Engineer specializing in NLP, LLMs, and RAG systems