Vetted Machine Learning Engineers in the DMV

“Backend engineer who built an AI-driven "Smart Feedback Analyzer" API (Flask → FastAPI) that processes user feedback with NLP (Hugging Face + OpenAI) and returns structured insights. Demonstrates strong production-minded architecture: stateless services, Cloud Run + Docker deployment, Redis/Celery background processing, and Postgres/SQLAlchemy performance tuning (EXPLAIN ANALYZE, indexing, N+1 fixes), plus multi-tenant data isolation via JWT/API-key derived tenant IDs.”

“ML/AI engineer with production experience in high-scale banking fraud detection at Truist, building an end-to-end pipeline (Airflow/AWS Glue/Snowflake, PyTorch/sklearn) with automated retraining and Kubernetes-based deployment; delivered measurable gains (22% fewer false positives, 15% higher recall) and reduced manual ops ~40%. Also partnered with clinicians at Kellton to deploy an LLM system for summarizing/classifying clinical notes, improving review time and decision speed.”

Sri Mounika Jammalamadaka

Screened

Mid-level AI/ML Engineer specializing in GenAI, LLMs, and data platforms

Fairfax, VA6y exp

“Built and helped deploy a production RAG-based LLM assistant for HVAC anomaly diagnostics, partnering closely with field engineers and operations teams to make AI outputs trustworthy in real workflows. Stands out for practical post-launch optimization work—improving retrieval quality, reducing hallucinations, and stabilizing non-deterministic behavior—which contributed to roughly a 40% reduction in diagnosis time.”

Aneri Patel

Screened

Junior Machine Learning Engineer specializing in LLM fine-tuning and semantic retrieval

Washington, D.C.2y exp

“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.”

Siddharth Ranjan

Screened

Mid AI/ML Engineer specializing in LLMs, RAG, and cloud AI systems

Maryland, USA4y exp

“Built an AI-powered job matching platform end to end using AWS, Gemini, FastAPI, TypeScript, embeddings, and vector search. The standout result was automating manual matching workflows and scaling resume processing to roughly 2,000 resumes per minute while monitoring quality with F1 score and latency metrics.”