Vetted Data Validation Professionals

Parth Gupta

Screened

Junior Robotics & Computer Vision Engineer specializing in perception and autonomy

Ames, IA2y exp

“Robotics engineer with capstone experience building an autonomous food-assembly robot arm, owning perception/deep learning (SAM2-based segmentation) and a model-based RL manipulation policy for deformable food items while also serving as project manager. As a robotics engineering intern at Salin247, optimized an autonomous farm vehicle perception stack to hit 20 FPS by cutting latency from 200ms+ to ~40ms using GPU acceleration (CUDA OpenCV, CuPy) and multiprocessing, and built ROS 2 nodes for real-time perception and streaming.”

“Data engineer with experience at Expedia building SQL Server and Azure Data Factory pipelines for business reporting and analytics. Stands out for pragmatic end-to-end pipeline ownership in ambiguous environments, with a strong emphasis on data quality, rerunnability, query performance, and making downstream datasets reliable for other teams.”

“Built and shipped production LLM agents that automate document processing and decision workflows, with a strong focus on reliability, guardrails, and measurable business impact. Stands out for combining RAG, tool calling, evals/monitoring, and ERP integration to deliver 30-35% manual effort reduction and higher throughput without additional headcount.”

“Software engineer with hands-on experience building end-to-end internal products at State Farm, spanning React/TypeScript frontends, AWS Lambda serverless backends, and Postgres data layers. Stands out for combining strong systems thinking with product sense: they improved a policy rerate platform with measurable performance gains, built a reusable rerate API adopted across teams, and also shipped an internal LLM chatbot MVP with built-in user feedback loops.”

“Backend/data engineer focused on compliance and statistical processing systems on AWS, building containerized FastAPI services plus event-driven async workflows (Step Functions/EventBridge) with strong reliability patterns (JWT auth, idempotency, structured logging). Has modernized SAS-based batch pipelines into modular Python/AWS services with parallel-run parity validation, and has demonstrated measurable SQL performance wins (40+ min to <10 min) and hands-on incident ownership using CloudWatch-driven detection and prevention.”

“Backend/data engineer with hands-on production experience across FastAPI/PostgreSQL APIs and AWS (Lambda, ECS) delivered via Terraform + GitHub Actions. Built Glue-based ETL pipelines into Redshift with schema evolution and data quality checks, modernized legacy reporting into Python microservices, and has demonstrated measurable SQL performance wins (multi-second query reduced to sub-300ms).”

“Built and deployed a production LLM/RAG fraud investigation system to replace manual investigator workflows, combining transaction data, historical cases, and policy documents with agent-style steps and LoRA fine-tuning. Demonstrates strong reliability engineering (grounding, citations, abstention paths), performance optimization (retrieval/indexing/caching), and end-to-end MLOps orchestration using Azure ML Pipelines/MLflow plus Kubernetes/Argo with canary and rollback deployments.”

“AI/ML engineer (Cognizant) who built a production, real-time credit card fraud detection platform combining deep-learning anomaly detection with an LLM-based explanation layer. Strong focus on regulated deployment: addressed class imbalance and feature drift, and added guardrails (SHAP/structured inputs, fine-tuning on analyst reports, rule-based validation) to keep explanations accurate and compliant. Orchestrated the full pipeline with Airflow + Databricks/Spark and used MLflow/Prometheus plus A/B and shadow deployments for measurable reliability.”

“Data/ML engineer with experience across pharma (Dr. Reddy Laboratories) and financial services (Cincinnati Financial, Capital One), building production NLP and entity-resolution systems that connect messy unstructured text with enterprise SQL data. Delivered semantic search with BERT + vector DB and domain fine-tuning (reported ~35% relevance lift), and builds robust pipelines using Airflow/dbt/Spark with strong validation, monitoring, and stakeholder-aligned rollout practices.”

Vivek Reddy

Screened

Mid-level Data Scientist/Data Engineer specializing in ML pipelines, insurance and healthcare analytics

Los Angeles, CA7y exp

“Built a production assistive-vision iPhone app to help visually impaired users find grocery items, training a custom YOLO detector on 2,000+ self-collected/annotated images and deploying via CoreML with a cloud multimodal LLM for navigation instructions. Brings hands-on AWS serverless + ECS container deployment (CDK/GitHub Actions) and a disciplined approach to AI workflow reliability (state-machine design, offline evals, stress tests, logging/metrics), plus experience communicating model insights to non-technical stakeholders (MOTER Technologies).”

Sakshi Dinesh Deore

Screened

Mid-level Software Engineer specializing in AWS, DevOps automation, and data platforms

Bellevue, USA3y exp

“Engineer with Securonix experience deploying and operating production microservices and real-time data-processing systems at high throughput. Led AWS infrastructure, CI/CD, monitoring, and customer-driven customization for a threat-report classification solution, including rule adjustments and model retraining based on live client feedback.”

Nicholas Moore

Screened

Senior Full-Stack Engineer specializing in scalable cloud-native systems

Lehi, Utah13y exp

“Backend/data engineer with production experience building high-concurrency customer engagement platforms at KomBea on AWS (EKS + Lambda) using FastAPI/Django, PostgreSQL, Redis, and strong observability. Has modernized legacy batch systems into modular Python services with parallel-run parity validation and phased rollouts, and has delivered resilient AWS Glue ETL pipelines with schema evolution and data quality controls.”

Geetha Sri Kasu

Screened

Mid-level Software Engineer specializing in Java/Spring Boot, Kafka, and AWS

5y exp

“Software engineer who owned an end-to-end self-service reporting workflow (secure APIs, async/batched processing, and React UI), improving report generation performance by ~30–40% and reducing manual support effort. Also built a RAG/embeddings prototype over internal docs and service logs with grounding-focused guardrails, and has a strong reliability/observability mindset (retries, DLQs, CI/CD validation, dashboards/tracing) for distributed workflows.”

“Entrepreneurial operator with 30+ years of experience building internal startup-style business cases inside private companies, securing capital/OpEx funding, and turning proposals into delivered technology initiatives. Brings a strong venture-informed mindset, including familiarity with Series A/B/C funding dynamics, combined with hands-on strength in business planning, financial modeling, team building, and execution.”

“Analytics-focused candidate with hands-on experience building SQL reporting tables from messy transactional and master data, plus Python workflows that automate monthly analysis and data checks. They appear strongest in KPI/reporting ownership, metric standardization, and stakeholder alignment, with examples of improving reporting consistency, surfacing issues earlier, and reducing manual reconciliation effort.”

Hargun Kaur Kohli

Screened

Intern Business Analyst specializing in analytics and marketing insights

California, USA1y exp

“Graduate-school capstone and project work centered on analytics, including healthcare shipment/pharmacy data, customer recommendation modeling, and a gaming uplift modeling project. Stands out for framing analytics around business impact—using uplift, repeat purchase, and profit-oriented metrics rather than just accuracy.”

Yash Patel

Screened

Mid AI/ML Engineer specializing in MLOps and cloud platforms

Texas, USA3y exp

“ML/AI engineer with strong end-to-end production ownership across classical ML and GenAI systems. Built and deployed predictive analytics and RAG-based internal tools on AWS/Kubernetes with measurable impact on accuracy, latency, deployment speed, safety, and user productivity.”

Carlos Morales

Screened

Director-level QA Manager specializing in AAA game testing, live services, and VR worlds

San Francisco, CA16y exp

“Game QA professional with ~5 years in embedded QA roles across major studios (Experis Game Solutions, Activision, Ubisoft, Meta), including ownership of the Weapons feature area on Ubisoft’s XDefiant and feature testing on Warzone. Known for risk-based, cross-system test coverage (matchmaking/party, progression, entitlements/MTX, performance across PC/console, live-service integrations) and for leading cross-discipline meetings and release readiness reviews.”