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Vetted Machine Learning Engineers in the DMV
Pre-screened and vetted in the DMV.
Senior Applied Machine Learning Engineer specializing in FinTech & E-commerce
Senior Applied Machine Learning Engineer specializing in FinTech & E-commerce
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and RAG for financial services
Mid-level AI/ML Engineer specializing in LLMs, RAG, and risk/fraud modeling
Mid-level AI/ML Engineer specializing in Generative AI, MLOps, and geospatial intelligence
Senior AI/ML Engineer specializing in computer vision, GenAI, and 3D spatial analytics
Diwita Banerjee
Mid-level AI/ML Engineer specializing in LLMs, RAG, and enterprise AI
“Built an enterprise RAG-based document intelligence system at Freddie Mac for regulatory and financial documents, helping analysts cut search time from hours to minutes while improving retrieval accuracy by ~30%. Stands out for combining LLM product delivery with compliance-grade auditability, production monitoring, and scalable Python/FastAPI service design.”
Principal AI Systems Architect specializing in agentic AI and enterprise platforms
Intern AI/ML Engineer specializing in computer vision and LLM systems
Senior Machine Learning Engineer specializing in MLOps, GenAI, and real-time systems
Mid-level Data Scientist / AI/ML Engineer specializing in NLP, CV, and MLOps in Financial Services
Mid-level Generative AI Engineer specializing in LLMs, RAG, and semantic search
Surya Pavan
Mid-level Machine Learning Engineer specializing in Generative AI and LLM applications
“GenAI engineer who has deployed production LLM/RAG chatbots for internal document search, focusing on reliability (hallucination reduction via prompt guardrails + retrieval filtering) and performance (latency improvements via caching). Experienced with LangChain/LangGraph orchestration for multi-step agent workflows and iterates using monitoring/logs and benchmark-driven evaluation while partnering closely with product and business teams.”
Rayyan Alam
Junior Robotics & Machine Learning Engineer specializing in autonomy and RAG systems
“New-grad robotics software engineer with hands-on ROS 2 autonomy experience (Nav2, SLAM Toolbox, AMCL) and a strong track record debugging real-world instability (QoS, lifecycle timing, sensor dropouts). Built an HRI speech system on a Stretch 3 robot with deterministic, context-aware templates to manipulate trust/competence/emotion conditions, and integrated an LLM high-level planner that outputs PDDL for classical task planning and replanning.”
Abhinav Vengala
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
“LLM/agentic systems engineer who built a production "Agentic AI Diagnostic Assistant" for network engineers, using a multi-agent Llama 2 + LangChain architecture with RAG over telemetry/incident data in DynamoDB and confidence-based deferrals to reduce hallucinations. Also has strong MLOps/orchestration experience (Airflow, EventBridge, Spark, Docker, SageMaker/ECS) at multi-terabyte/day scale and delivered multilingual NLP analytics (fine-tuned BERT/spaCy) for support operations through hands-on stakeholder workshops.”
DEDEEPYA PALAKURTHI
Mid-level AI/ML Engineer specializing in LLMs, RAG, and enterprise MLOps
“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.”