Vetted Model Evaluation Professionals

“Backend engineer who evolved the X-Ray gaming analytics platform, leading a zero-downtime MongoDB→AWS DocumentDB migration with dual-write, checksum-based validation, and Kubernetes canary rollouts while maintaining real-time monitoring for millions of concurrent sessions. Strong in FastAPI/Python API scaling and performance tuning (cut latency from ~2s to <150ms and reduced DB load 90%) plus production-grade auth/RLS security patterns (JWT, Supabase Auth, PostgreSQL RLS).”

Sourabh Jain

Screened

Director of Software Engineering specializing in enterprise Data, ML & AI platforms

Bay Area, CA23y exp

“Former Walmart Director of Software Engineering who left in March 2025 to build products for clients. Recently delivered an LLM/RAG-based UNSPSC classification solution for an MRO client using a multi-stage retrieval + web search + prompt-engineering workflow, and has led large-scale retail forecasting initiatives and high-severity cloud-migration incidents end-to-end.”

“Engineer with hands-on experience across backend, full-stack, cloud, and AI/ML systems, with particular depth in Python, FastAPI, AWS Bedrock, SageMaker, and RAG-based architectures. Stands out for treating AI and agents as accelerators within disciplined production engineering, emphasizing guardrails, observability, latency/cost monitoring, and scalable system design.”

“Research Extern at Google DeepMind and former AWS Software Development Engineer Intern with a strong focus on practical, trustworthy AI engineering. Built a multi-agent RAG system for personalized news headline generation using a fine-tuned Flan-T5 model, parallel critic agents, FAISS retrieval, and style embeddings, while also leading a 3-person team on the project.”

Likhitha Bethi

Screened

Mid-level Software Engineer specializing in backend systems, distributed systems, and applied AI

Stony Brook, NY4y exp

“Goldman Sachs engineer who owned end-to-end features for an internal onboarding and case management platform, spanning React/TypeScript UI, a GraphQL gateway, and Node + Spring WebFlux microservices. Built and operated a Kafka-based ingestion and search pipeline with DLQs, retries, idempotency, and strong observability, and improved developer experience via backward-compatible GraphQL API design and schema-driven documentation.”

“Robotics software engineer from Ati Motors who brought a Linear MPC approach (based on Kuhne et al.) into production, rebuilding parts of the planning stack to eliminate oscillations and safely double AMR speed from 0.8 m/s to 1.6 m/s. Also delivered an end-to-end point-cloud detection pipeline (PointPillars) including synthetic data generation in Isaac Sim and TensorRT deployment for real-time human/trolley detection, with a strong focus on production reliability via iterative hardening and nightly SIL.”

“Built GenMedX, a multi-module clinical AI system for emergency department decision support spanning triage prediction, diagnosis, medication Q&A, and visit summarization. Stands out for combining medical LLM fine-tuning, RAG, and rigorous evaluation/monitoring to drive a major triage recall improvement from 38.5% to 76.6%, with a strong focus on safety, edge-case detection, and production reliability.”

“Built a production internal knowledge assistant using a RAG pipeline over large spreadsheets, PDFs, and support documents, using transformer embeddings stored in FAISS. Focused on real-world production challenges—format normalization, retrieval quality, hallucination reduction (context-only + citations), and latency—using hybrid retrieval, quantization, and containerized deployment, and communicated the workflow to non-technical stakeholders using simple analogies.”

“Built a production LLM-driven archival assistant that turns large, low-quality scanned handwritten files (120+ pages) into structured datasets, overcoming context-window and hierarchy challenges with a two-phase LLM + rules pipeline and reaching 98.1% accuracy (Gemini-2.5 Flash). Also orchestrated a large human-in-the-loop effort with 78 archivists, producing 2,400 high-quality annotations in 4 days via detailed rubrics and support.”

“Senior engineering leader in the Bay Area with experience spanning VMware, Hortonworks/Cloudera, Barracuda, and Palo Alto Networks, including leading open-source work (Apache Knox) and architecting large-scale security platforms. Has driven disaster recovery and cloud security products, designed Python microservices for Microsoft 365 security, and scaled teams (3x) while formalizing enterprise readiness practices with automated documentation using Notebook LLM.”

Daniel Luzzatto

Screened

Junior Machine Learning Engineer specializing in LLMs, computer vision, and robotics

Tirat Carmel, Israel1y exp

“Built and deployed an agentic, multimodal LLM system that automates privacy redaction pipelines (audio/video/tabular) using LangChain orchestration and a closed-loop self-correction design. Personally implemented and performance-optimized core CV tooling (face blurring with tracking/Kalman filter) achieving >100 FPS on CPU, and validated reliability with golden-dataset benchmarking across 100+ privacy intents and measurable redaction metrics.”

Yash Jajoo

Screened

Senior Software Engineer specializing in AI and FinTech platforms

New York City, NY8y exp

“Built a production LLM pipeline at Walter AI that scans massive user inboxes, identifies financial newsletters, and extracts trading strategies into structured JSON for downstream paper-trading workflows. Stands out for combining agent architecture with strong production discipline—cutting scan time from 20 to 5 minutes, reducing LLM costs by 90%, and achieving 3-second P99 latency while handling messy, inconsistent email data at scale.”

Robert Davis

Screened

Staff Software Engineer specializing in backend and distributed systems

Remote, US19y exp

“Backend engineer who co-launched SkyKick’s Office 365 SharePoint/Exchange backup product, built the MVP, and then architected and led its design for 9 years. Stands out for high-scale systems expertise, including an algorithmic redesign that cut cloud costs by an order of magnitude, plus earlier experience integrating speech recognition systems in noisy real-world customer environments.”

“Built a production RAG-based "knowledge copilot" for support/ops using LangChain/LangGraph, implementing the full pipeline (ingestion, chunking, embeddings, vector DB retrieval/rerank, guarded generation with citations) and operating it as monitored microservices with CI/CD. Also designed an event-driven, streaming backend for real-time inventory ordering predictions that reduced stockouts by 25%, and has hands-on incident response experience stabilizing LLM API latency/5xx spikes using Datadog/APM and resilience patterns.”