Pre-screened and vetted.
Senior AI/ML Engineer specializing in Generative AI, RAG, and multimodal LLM systems
Junior AI Engineer specializing in NLP, LLMs, and recommender systems
Senior Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Generative AI Engineer specializing in RAG systems and AI-powered education tools
Entry-Level Software Engineer specializing in AI/NLP and full-stack development
Senior Full-Stack & AI Engineer specializing in FinTech and Healthcare
Senior Data Engineer specializing in Machine Learning and Healthcare Data Platforms
Mid-level Generative AI Engineer specializing in LLMs, RAG, and NLP systems
Senior Full-Stack Python Engineer specializing in AI/LLM-powered web applications
Senior Full-Stack Software Engineer specializing in AI/LLM-powered web applications
Entry-Level AI Engineer specializing in NLP and LLM-powered applications
“AI engineer who built an agentic, production-deployed LLM workflow for tobacco violation parsing and automated multi-case creation, using six specialized agents and a human-in-the-loop confidence-threshold routing design. Addressed data privacy constraints by generating synthetic datasets with LLM prompting, and orchestrated reproducible end-to-end pipelines in LangChain with robust testing and evaluation (precision/recall, micro-F1).”
Mid-level Software Engineer specializing in Generative AI and scalable backend systems
“Backend/AI engineer with production experience in legal tech: built a high-scale licensing/subscription API (FastAPI/Postgres/Stripe) and shipped a RAG-based chatbot for an eDiscovery platform. Designed a robust legal document ingestion workflow that processes thousands of documents into a searchable vector index with clear retry/escalation logic, and has demonstrated measurable Postgres performance wins (200ms to 10ms) using EXPLAIN ANALYZE and composite indexing.”
Junior AI/Software Engineer specializing in NLP, RAG, and resume parsing
“Backend/AI engineer who built and refactored a production RAG system over IRS Form 990 filings for 60 nonprofits, using a dual-path architecture (deterministic financial ranking + TF-IDF semantic retrieval) to keep latency sub-2s and reduce hallucinations. Demonstrates strong API craftsmanship in FastAPI (contract-first, OpenAPI-driven) plus production-grade security for multi-tenant systems (JWT, RBAC, Supabase-style RLS) and careful migration practices (feature flags, traffic mirroring, incremental rollout).”
Mid-level AI Engineer specializing in LLM agents, RAG, and data pipelines
“Built and productionized LLM-powered workflows that generate contextual insights from structured financial data, including prompt/retrieval design, data standardization, and reliability controls like rate limiting and batching. Also diagnosed and fixed real-time failures in an automated order validation system using logs/metrics, staging reproduction, edge-case handling, retries, and alerting, while supporting sales/customer teams with demos, scripts, and FAQs to drive adoption.”
Mid-level Data Scientist specializing in Python, ML, and BI dashboards
“Data/NLP practitioner who builds production-oriented pipelines for unstructured text: entity extraction, topic modeling (LDA/BERTopic), and semantic search using Sentence-BERT embeddings with FAISS. Emphasizes rigorous evaluation (coherence/silhouette + manual review), entity resolution with validation, and scalable workflow orchestration using Airflow/Prefect with Spark/Dask.”
Mid-level AI Engineer specializing in agentic systems and enterprise LLM platforms
“Current AI engineer at a startup who has spent the last year architecting multi-agent systems for software development workflows. Stands out for combining LLM speed with engineering discipline—using tools like Pydantic, LangGraph, and LangChain to build reliable, production-ready agent workflows with validation, routing, and retry logic.”
Junior Data Scientist specializing in applied ML, LLMs, and analytics automation
“Research Analyst at Syracuse who deployed an LLM-powered lab automation system allowing researchers to run QCoDeS instrument workflows via natural language, with strong safety guardrails for real instruments and multi-instrument support. Also collaborated with non-technical stakeholders at iConsult on an audio classification/recommendation pipeline, translating business goals into metrics and Tableau dashboards with model comparisons and A/B test results.”
Entry-level Data Scientist and Software Engineer specializing in AI and data pipelines