Vetted CSS Professionals

Rodolfo Garcia

Screened ReferencesStrong rec.

Senior QA Test Analyst specializing in game and service testing

Los Angeles, CA11y exp

“Game QA/automation tester with experience at Blizzard, Bossfight Entertainment, and Netflix, spanning manual-to-automation transitions, Selenium/C# UI automation, and CI/CD nightly reporting via TestRail. Known for an end-user-driven test strategy, strong defect isolation (including crash dumps), and cross-functional test planning that influenced multiplayer UX/design decisions.”

“Software engineering intern who built an internal AI-agent automation using the Gemini API to reduce manual CRM data entry, iterating prompts closely with analysts to address precision concerns. Also worked on a medical image-diagnostics LLM project involving fine-tuning and benchmarking multiple model approaches, and has quant/sales-trading experience building automated pricers for complex options and persuading sales teams to adopt them with ROI-focused metrics.”

“Project lead who partners with PM and customers to gather requirements, adjust project plans, and deliver new functionality that drives customer satisfaction and revenue. Has experience building features end-to-end and presenting successful technical demos to engineering and management audiences; no stated experience with LLM/agentic systems.”

“Built and productionized a real-time enterprise RAG pipeline to improve factual accuracy and reduce LLM hallucinations by grounding responses in constantly changing internal knowledge bases (policies, manuals, FAQs). Experienced in orchestrating end-to-end ML workflows (Airflow/Kubernetes), handling messy multi-format data with schema enforcement (Pydantic/Hydra), and maintaining freshness via streaming incremental embeddings plus batch refresh. Also delivers applied ML solutions with non-technical teams (marketing/CRM) for segmentation and personalized engagement.”

“Backend engineer who helped redesign and refactor Forma’s backend during an app rewrite, emphasizing modularity, maintainability, and A/B testing support while delivering feature parity on a quarter-long timeline. Led a careful database migration using parallel databases with schema differences, validating integrity via staging and SQL checks, and has experience debugging subtle computer-vision overflow edge cases.”

Akshitha Singireddy

Screened

Junior Software Engineer specializing in data engineering and computer vision

Bellevue, WA1y exp

“Former Amazon intern who owned an end-to-end computer vision system to detect package anomalies in fulfillment centers, from data collection/labeling to production deployment on AWS (EC2/S3) with a Streamlit live-monitoring dashboard. Also has ML-in-production experience deploying and updating a recommendation model on Kubernetes (Minikube) with CI/CD via GitHub Actions, plus prior SDE experience with Jenkins-based pipelines and on-prem to AWS migration work using Glue.”

“Meta engineer who improved a critical revenue estimation dataset pipeline that was arriving ~6 days late—diagnosed via raw logs/lineage, redesigned legacy scans to only process the needed window, and shipped validation plus freshness/lag dashboards. Delivered ~50% latency reduction (to ~3 days) and regained adoption by running old/new pipelines in parallel with gated cutover and evidence-based customer communication. Applies incident-response rigor to real-time LLM/agentic workflow debugging and regularly runs developer demos/workshops.”

“Backend engineer who scaled a food delivery platform by migrating from a single-service architecture to Spring Cloud microservices with an API gateway and Kafka-based event-driven order pipeline. Reported outcomes include ~50% latency reduction, stable ~2K RPS throughput, and 99.8% uptime, with strong emphasis on safe migrations (dual writes, canaries, schema versioning) and security (JWT/RBAC/Postgres RLS).”

Timothy Mazenge

Screened

Mid-Level Software Engineer specializing in Ads frontend and high-scale web platforms

Kirkland, WA6y exp

“Backend engineer with ad-tech experience who improved advertiser dashboard accuracy by exempting 1% of traffic from ML-based dropping in a ~1B-requests/day pipeline, trading storage for higher customer satisfaction and reduced debugging load. Demonstrates strong migration discipline (phased rollouts, compatibility layers, rollback/change-history recovery) and production API/security practices in Python/FastAPI (async, caching, throttling, RBAC/RLS, monitoring).”

Ahmed Sadaqat

Screened

Senior Machine Learning Engineer specializing in production ML and predictive analytics

Los Angeles, CA7y exp

“ML/AI engineering leader who has owned end-to-end production systems from experimentation through deployment, monitoring, and iteration at meaningful scale. They describe running a 1M+ records/day prediction platform with 99.9% availability, shipping a RAG-based conversational AI feature for 50,000 active users, and consistently improving precision, latency, reliability, and cost with measurable business impact.”

“Backend/data engineer with hands-on production experience across GCP (FastAPI microservices on Kubernetes) and AWS (Lambda, ECS Fargate, Glue). Has modernized legacy SAS batch systems into Python services with parallel-run parity validation, and has strong operational rigor in ETL reliability/monitoring plus proven SQL tuning impact (25s to <300ms, ~60% CPU reduction).”

“Built and shipped a production LLM-powered medical scribe that generates structured clinical visit summaries using RAG, strict JSON schemas, and post-generation validation to reduce hallucinations. Experienced in making LLM workflows deterministic and observable (structured logging/metrics/tracing) and in evaluation-driven iteration with metrics like schema pass rate and edit rate; collaborated closely with clinicians and policy stakeholders at Scale AI to drive adoption.”