Vetted SQL Professionals

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.”

Jingfei Xu

Screened

Intern/Junior Software Engineer specializing in AI/ML and cloud-based systems

Mountain View, CA0y exp

“Embedded/robotics software engineer with Hyundai Motors experience who owned an AI-driven perception validation pipeline using a Transformer-based approach to generate stable synthetic in-cabin audio for autonomy/ASR testing, cutting downstream testing time by 50%+. Has hands-on ROS integration (IMU sensor streaming, inference, control nodes), MQTT-based distributed messaging, and cloud/container deployment experience (Docker, Node/Express, AWS, CI/CD).”

“Senior software engineering leader with 20+ years of management exposure who has alternated between IC and director-level roles, leading teams of up to 25 across AI platform, analytics, Salesforce, and systems software projects. Particularly compelling for roles needing both technical depth and organizational leadership: they have architected systems themselves, built teams in new geographies, and coordinated platform, AI/data, and consumer engineering groups to deliver successful turnkey AI solutions.”

john emerson

Screened

Executive product and AI leader specializing in healthcare, public health, and EdTech

Boulder/Denver, CO15y exp

“Veteran healthtech product leader with a track record spanning consumer health, provider workflows, AI voice agents, and public-sector pilots. They have led both large-scale rebuilds and 0-to-1 products, including work tied to Healthline's $21M Series B, a major Healthgrades revenue platform overhaul, and AI healthcare operations products—while consistently emphasizing human-centered design and measurable outcomes.”

“Engineer with startup experience spanning fintech and B2B SaaS, from Playd during rapid growth to Clarity’s AI-powered contract review platform. Particularly strong in React/TypeScript product development for complex, data-heavy workflows used by accountants and finance teams, with supporting experience in Node, Postgres, AWS, and production database design.”

“Robotics/ML engineer with internship experience at Valeo building a deep-learning prototype to replace parts of a legacy SLAM backend for autonomous parking, focused on making models run reliably in real time on embedded hardware (quantization/distillation + TensorRT). Also brings strong MLOps/deployment experience (Docker, Kubernetes on AWS EKS, CI via GitHub Actions) and has supported patent filing by explaining the technical approach to legal stakeholders.”

“Performance marketing analyst at Meta supporting Amazon who identified Amazon app users as a high-value segment (2x ROAS), built and validated a retargeting audience via rigorous A/B testing, and helped drive a global rollout across thousands of campaigns resulting in ~$80M annual revenue. Strong in experiment design, SQL-driven insight generation, and translating performance learnings into cross-platform creative and catalog strategy.”

“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.”

“Internship at BlueFoxLabs building and deploying an AI/ML RAG system for a biopharma client on top of LibreChat, including an AWS Textract ingestion pipeline and PGVector retrieval deployed to AWS EKS. Demonstrated production-minded scalability work by moving from a vertically scaled EC2 setup to a horizontally scaling Kubernetes/EKS deployment, using CI/CD to safely incorporate requirement changes like tabular document data.”

“ML/NLP practitioner and technical founder who built an AUP risk-scoring model at Bill.com using TF-IDF + SVD features with XGBoost, and previously created automated data-quality guardrails for a Global Equity Risk stacked ML model at Thomson Reuters. Recently built a RAG-based chatbot for PaymentJock’s Home Affordability Probability product using embeddings and a local vector database (FAISS/Chroma), improving answer quality through chunking rather than expensive fine-tuning.”

“Chief of Staff to the COO / Strategy & Business Development leader at Annapurna who unified four distinct entertainment verticals (film, TV, interactive, theatre) into the company’s first cross-functional five-year plan. Built standardized pipeline reporting, forecasting models grounded in real execution rates, and executive dashboards that improved decision-making speed and COO leverage while navigating creative/finance tension and sensitive information.”

“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).”

Ravikanth Kasamsetty

Screened

Executive AI/ML Engineering Leader specializing in cloud-native SaaS and GenAI platforms

23y exp

“Engineering leader who modernized and unified a fragmented product suite at Milestone via a multi-year cloud-native roadmap, delivering an MVP in three quarters and boosting team velocity by 40% through cross-functional squads. At Prometheum, led a trust-building hybrid architecture (AWS control plane + customer-hosted data plane) using Kubernetes to ensure sensitive enterprise data never left customer networks while remaining cloud-agnostic across providers.”

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.”

Kieron Ong

Screened

Junior Software Engineer specializing in AI platforms and full-stack systems

New York, NY2y exp

“Frontend/product engineer with strong experience building sophisticated AI-assisted browser UIs for customer support operations in healthcare/therapy contexts. Particularly compelling for teams needing someone who can combine modern web architecture, observability, typed systems, and human-in-the-loop AI UX to improve both reliability and agent efficiency.”

“Backend/data engineer with Amazon supply-chain experience building production serverless Python services and ETL pipelines on AWS (Lambda, API Gateway, S3, RDS, Glue). Has modernized legacy SAS jobs into Python with rigorous parity testing and phased migrations, and has delivered major SQL performance gains (minutes down to seconds) through indexing and partitioning.”

“Backend/data engineer from Oscar Health specializing in healthcare claims systems on AWS. Built HIPAA-compliant real-time services (FastAPI/Postgres/Kafka on EKS) and serverless ingestion pipelines, and led modernization of a legacy SAS claims pricing system to Python/Spark with rigorous parity validation. Demonstrated measurable impact with high uptime/low latency services and major Snowflake performance and cost reductions.”

“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.”

“Built and shipped a real-time AI phone agent for small businesses that handles bookings/FAQs/messages using streaming ASR, an LLM with tool-calling, and TTS; deployed to production for multiple paying customers. Demonstrates strong applied LLM reliability practices (tool-first grounding, retrieval, hard-negative testing, and production monitoring) and experience orchestrating multi-step AI workflows with Airflow, Prefect, and AWS Step Functions.”

“Chief of Staff to the COO of firmwide engineering at Goldman Sachs, serving as lead strategist for a COO/CIO-sponsored program to drive operational excellence and scalability via AI/automation. Ran discovery across divisions, built governance/OKR systems, negotiated budget commitments with divisional leaders, and coordinated firmwide CFO alignment while preparing Board-level materials for executives.”

“Robotics software candidate with hands-on experience building controllers for an Autonomous Underwater Vehicle, including dual-PID control in Python with state-space modeling and a planned path to LQR. Developed ROS nodes for odometry-based localization, waypoint planning, and control command publishing, validated through a custom Gazebo/ROS simulation workflow with control-metric-driven testing. Also worked on F1Tenth simulation and scan-matching localization (PL-ICP), with additional cloud deployment experience using Docker/Kubernetes and CI/CD.”

“Gameplay engineer with shipped mobile multiplayer experience on Squid Game: Unleashed, where they owned the Usable Items system end-to-end in Unity/C#. Built a modular ScriptableObject/action-based architecture that let designers create new item behaviors quickly without engineering support, while also handling network sync, prediction-related debugging, and internal validation tooling as the content library scaled.”

“Fintech and AI product engineer who has owned major production rollouts, including Lending Club's banking-arm launch, and has since built LLM-powered decision systems for finance and climate use cases. Particularly strong in combining stakeholder management with pragmatic architecture choices like observability, deterministic pipeline design, RAG, and document-to-structured-data workflows.”