Vetted Research Assistants in the DMV

“Former Special Assistant at the National Security Council with experience supporting senior federal executives and handling national-security-sensitive information. Helped stand up and standardize operations for a large-scale refugee resettlement effort (60,000 people), creating an executive-driven exception/escalation process and partnering with dev and data teams to prioritize agile sprint work and improve reporting accuracy.”

“IFC professional who helped build a supply chain decarbonization fund, running multiple workstreams spanning TA program design, MRV framework build-out, gender inclusion, supplier pipeline development, investor engagement, and engineering partner coordination. Known for critical-path prioritization and executive-ready operating systems (decision trackers, weekly one-page briefs, risk logs) that keep complex, multi-stakeholder initiatives aligned and moving quickly.”

“Robotics software/perception engineer with production AMR experience at Symbotic, building a real-time SKU case re-identification pipeline used in high-volume Walmart/Target warehouse operations. Strong in ROS2 + Docker deployments on Jetson (TensorRT quantization) and system-level performance debugging, including cutting inference latency from ~13s to ~2s through architecture changes. Also has lab experience integrating SLAM/MPPI/behavior trees for rule-compliant navigation and distributed perception-to-UR5e manipulation systems (MoveIt/ros_control) with multi-camera sensing and 3D reconstruction.”

“Appian consultant/engineer focused on insurance and financial services modernization and AI-enabled workflows. Built and productionized an AI-driven insurance submission intake system (email ingestion, classification/extraction, HITL review) cutting processing time from 2+ hours to under 10 minutes, and delivered semantic smart search with guardrails and UAT-driven ranking improvements. Also partnered with a global bank CTO org, running sessions with 200+ senior leaders to automate regulatory/board metric reporting via platform integrations and attestation.”

“Robotics software engineer who built and owned an autonomous laparoscope tracking system on a UR3e with an eye-in-hand RealSense camera, integrating YOLO-based tool detection with velocity control under a strict RCM constraint and deploying successfully in a hospital setting. Deep ROS2/MoveIt2 experience (architecture, QoS, custom nodes) plus autonomy stack work across SLAM, planning, and real-time latency/control debugging.”

“Built and launched a production self-healing MLOps agent that autonomously diagnosed and fixed model training failures on Kubernetes GPU infrastructure. Combines deep AI infrastructure knowledge with full-stack product ownership, and has delivered measurable impact including 35% less infrastructure waste, nearly 50% less troubleshooting time, and 60% lower LLM API costs.”

“ML/AI engineer focused on production NLP and voice AI systems in the restaurant tech space, with hands-on work spanning ASR, intent classification, LLM fine-tuning, and deployment monitoring at Presto AI. They highlight a 15% improvement in full-AI ordering rate and also built a restaurant sentiment analysis product at Wisely that they say became a standout feature in a $10M acquisition context.”

“Research-focused AI engineer who built an agentic pipeline to automatically extract Sphinx-based API documentation/changelogs and generate synthetic tasks for a dynamic LLM code benchmark targeting real-world API evolution and deprecations. Experienced with multi-agent orchestration (AutoGen, LangChain, CrewAI) and rigorous evaluation methods, and has prior multi-agent work from a Microsoft Research internship.”

Vineet Jujjavarapu

Screened

Mid-level Software Engineer specializing in cloud-native data platforms

College Park, MD3y exp

“Software engineer with hands-on experience using AI coding assistants and LangChain-based agent workflows in RAG/LLM projects. Stands out for combining practical multi-agent experimentation with strong grounding in system design, distributed systems, and production-minded validation of AI-generated outputs.”

“Backend/full-stack engineer at Qualcomm who built and operated a drift monitoring platform for 10k+ edge AI models. Stands out for combining strong TypeScript/React/Node execution with production-grade systems thinking across PostgreSQL tuning, Redis caching, ECS deployments, and Kafka-based architectural improvements that measurably improved reliability and release speed.”