.png){kind=logo}
Vetted Data Validation Professionals
Pre-screened and vetted.
Senior AI/ML Engineer & Data Scientist specializing in NLP, entity resolution, and knowledge graphs
Mid-level Data Engineer specializing in AI/ML and cloud data platforms
Senior Software Engineer specializing in backend APIs and regulated FinTech workflows
Intern Software Engineer specializing in full-stack web and mobile development
Senior Software Engineer specializing in full-stack platforms and cloud services
Junior Data Analyst specializing in experimentation, data quality, and ML analytics
Mid-level AI/ML Engineer specializing in RAG, NLP, and MLOps
Bocheng Wan
Mid-level Software Engineer specializing in consumer robotics and machine learning
“Developer with a structured AI-assisted coding workflow centered on algorithmic rigor, type-safe scaffolding, and spec-driven modular design. Used Claude Code to help build an Android SDK for IPC, quickly ramping up on AIDL and compressing delivery including unit tests from several weeks to two weeks.”
Matthew Zhan
Senior Full-Stack Engineer specializing in SaaS, distributed systems, and FinTech workflows
“Full-stack engineer with strong startup experience across small distributed teams, owning everything from React UIs to Go services and Python data pipelines. He stands out for designing stable APIs and data models in ambiguous compliance-heavy environments, with measurable impact including a 38% reduction in manual cleanup and a 27% drop in customer-visible incidents. He has also worked deeply in B2B SaaS at Ashby, supporting mission-critical recruiting workflows where data correctness, permissions, and integration stability were essential.”
Harish Kasu
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”
Gabriel Undrerwood
Engineering executive specializing in production ML systems and enterprise SaaS
“Engineering/data platform leader from FLYR (airline ML forecasting and automated pricing) who built scalable ingestion/ETL and a canonical data model to onboard airlines with highly heterogeneous source systems. Created a golden-metrics layer for airline KPIs and implemented monitoring/backfill capabilities, cutting onboarding time by 50%+ while improving SLA performance and controlling cloud/ML training costs through stronger data quality gates.”
Vinay Ramrupe
Mid-level AI/ML Engineer specializing in LLM and enterprise generative AI
“ML/AI engineer focused on taking LLM systems from experimentation to reliable production, including enterprise copilot and RAG-based knowledge retrieval use cases. Stands out for combining data pipelines, model training, inference optimization, automated evaluation, and safety guardrails, with cited impact including 20% throughput gains and 30% less manual evaluation effort.”
Executive technology leader specializing in data platforms, cloud, and AI/ML
Mid-level AI/ML Engineer specializing in LLMs, RAG, and production MLOps
Mid-level Software Engineer specializing in backend, ML platforms, and FinTech
Senior AI Engineer specializing in LLM systems and scalable backend platforms
Senior Full-Stack Engineer specializing in FinTech compliance systems
Senior Full-Stack Engineer specializing in Unity/C# and AI-driven VR/mobile healthcare systems
Pankaj Gupta
Executive engineering leader specializing in AI, data infrastructure, and cybersecurity
“Senior engineering leader with deep hands-on experience building and scaling high-throughput platform infrastructure, including a Qualys core data platform using Kafka, Cassandra, OpenSearch, Ceph, and API gateways. He combines architecture depth with people leadership, and has led complex cross-team initiatives such as rolling out a Kubernetes-based container platform across 20 application teams using a phased migration strategy.”
Manaswini Gogineni
Mid-Level Software Engineer specializing in cloud infrastructure and full-stack web development
“Backend engineer at Electric Hydrogen who built a serverless device-log ingestion and processing platform in Python/Flask, scaling throughput (4x peak ingestion) while keeping sub-300ms API latency. Strong in Postgres/SQLAlchemy performance (partitioning, materialized views) and production ML integration (ONNX model served via FastAPI microservice with async batch inference, Redis feature caching, and drift monitoring via S3/Lambda). Experienced designing secure multi-tenant systems with schema-per-tenant isolation and KMS-backed encryption.”
Jolie Qiu
Mid-Level Software Engineer specializing in AWS data infrastructure and pipeline automation
“AWS-focused software engineer who built a self-serve ETL pipeline scheduling service for non-engineers, including automated CloudFormation-based onboarding that cut setup time from 2–3 weeks to ~5 minutes. Strong in production reliability and customer-facing data platforms (EMR/DynamoDB/Lambda), with examples spanning pagination at scale, cross-table consistency, and phased rollouts to improve Parquet log SLAs.”
Joseph Fusco
Senior Software Engineer specializing in AI-powered developer tooling and backend platforms
“Backend/product engineer from Postman Flows who has owned complex platform features end-to-end, including production versioning and an LLM-powered flow-building orchestration layer. Stands out for combining product-minded backend design, agentic AI workflow implementation, and strong production reliability work, including re-architecting a failing event pipeline from in-memory to managed queues.”