Vetted Anomaly Detection Professionals

“At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.”

“Data/ML practitioner focused on healthcare data quality and record linkage: analyzed 10M+ records, built anomaly detection and NLP-driven entity resolution, and automated AWS ETL/validation pipelines (Glue/Redshift/Lambda), cutting data errors by 40% and generating $500k in annual savings. Has hands-on experience with embeddings (Sentence Transformers/spaCy), FAISS vector search, and fine-tuning for domain-specific matching.”

“Built and deployed a production RAG-based LLM Q&A and summarization platform for internal documents, emphasizing grounded answers with structured prompting and citations to reduce hallucinations. Experienced orchestrating end-to-end LLM workflows with LangChain plus cloud pipelines (Azure ML Pipelines, AWS), and runs iterative evaluation using both metrics (accuracy/hallucination/latency/cost) and real user feedback to drive reliability.”

“Built and productionized LLM-driven sentiment scoring for earnings call transcripts at Goldman Sachs, replacing legacy NLP to deliver a cleaner trading signal while managing latency/cost via batching, caching, and distilled models. Also implemented an Airflow-orchestrated fraud modeling pipeline at MetLife with drift-based retraining and SageMaker deployment, and has a disciplined evaluation/rollout framework for reliable AI workflows.”

“Industrial AI/ML practitioner with experience deploying real-time monitoring and anomaly detection in a regulated Sanofi vaccine manufacturing facility, including root-cause workflows, logging/alerting, and SOP-aligned validation—achieving ~90% faster anomaly detection. Also built Python/NLP-style automation to accelerate instrumentation & control documentation (~40% faster) and delivered end-to-end predictive analytics for an agri-food operations/distribution client using close operator and leadership feedback loops.”

“Robotics software engineer who built the full control stack for a fleet of manufacturing/repair robots in Relativity Space R&D (perception, planning, motion control, integration, deployment). Has ROS/ROS 2 experience spanning custom SLAM (LiDAR+IMU), multi-robot coordination, and multi-drone control (Pixhawk 4, minimum-snap trajectories), with strong real-world debugging and simulation/CI testing practices (Gazebo, CI/CD, some Docker).”

“Full-stack engineer with strong Next.js App Router + TypeScript experience who built and owned a production internal analytics dashboard end-to-end, including server-component data fetching, route handlers for secure proxying, and post-launch monitoring/caching fixes. Also designed Postgres data models and performance-tuned analytics queries, and built reliable BullMQ/Redis-based order-fulfillment workflows with idempotency, retries, and compensating refunds—comfortable operating with high ownership in early-stage teams.”

“Backend/ML systems engineer with experience at SDSC, UCSD, and Media.net, building production semantic dataset/model discovery using embeddings + Solr KNN and LLM-based intent/reranking at 5M+ dataset scale. Emphasizes offline/online separation for predictable serving, has delivered measurable gains (23% retrieval accuracy, 38% latency reduction) and helped secure a $3M+ NSF grant.”

“Engineering leader from Blackline who has repeatedly rescued and delivered high-visibility products by resetting roadmaps, tightening execution (better specs/estimation), and accelerating team velocity. Scaled a distributed org from ~20 to ~40 engineers by building a new India team with strong hiring rubrics and governance-as-code/SDLC consistency. Also modernized legacy systems into microservices (Kafka/Kubernetes/Apigee) and drove hackathon-to-production innovation using Google Vertex AI.”