Vetted Computer Vision Professionals

Venu Dave

Screened ReferencesStrong rec.

Junior Software Development Engineer specializing in backend data platforms and LLM applications

New York, NY3y exp

“Amazon internship experience building and shipping an end-to-end NL-to-SQL system: ingested/normalized metadata across 60+ internal tables, added rigorous multi-layer validation for LLM-generated SQL, and served it via a FastAPI backend for engineers—driving 90%+ faster dataset discovery and ~70% lower effort to access data. Also built an early-stage RAG-based healthcare assistant, iterating on chunking, embeddings, and retrieval to improve answer quality post-launch.”

“Seasoned global CTO and executive leader with 20+ years of experience, including a $389M non-founder exit to a Fortune 10 acquirer. Now building a pre-seed AI-driven diagnostic imaging platform for pets with web and mobile products, beta customers, and a patent-pending solution aimed at saving pet lives.”

“Backend/data engineer focused on production ML/LLM systems: built a real-time FastAPI inference API on Kubernetes with strong reliability patterns (timeouts, idempotent retries, centralized error handling). Delivered AWS platforms using EKS + Lambda with GitHub Actions/Helm CI/CD and built Glue-based ETL from S3/Kafka into Snowflake with schema evolution and data-quality controls; also modernized legacy analytics/recommendation workflows into Python services with safe, feature-flagged cutovers.”

“Engineering leader (12+ years Director, 17 years lead) focused on developer productivity and platform/framework work across Oracle, PlayStation, Workday, and CafePress. Notable for building distributed teams from scratch and delivering high-impact platform architecture—e.g., re-architected PlayStation’s upload pipeline to support 500GB–5TB submissions using browser-to-AWS chunked uploads with SNS/SQS and deduplication/resume support.”

“ML/LLM engineer who has built and productionized a large multimodal LLM pipeline end-to-end—fine-tuning a 20B+ parameter model with distributed/FSDP training and deploying on Kubernetes via Triton for ~5x throughput. Strong focus on reliability and safety (monitoring with SHAP, guardrails, A/B testing) with reported ~22% relevance lift and reduced harmful/incorrect outputs, plus experience orchestrating ETL/retraining workflows with Airflow across S3/Snowflake/RDS.”

“Built and deployed a production LLM-powered clinical support assistant at BJC HealthCare (RAG + transformer) to answer patient questions, summarize clinical notes, and support appointment workflows. Implemented PHI-safe data pipelines (Spark/Hadoop/Kafka) with automated scrubbing, dataset versioning, and audit logs, and runs the system on Docker/Kubernetes with Pinecone vector search while partnering closely with clinical operations staff.”

“VC-focused sourcing candidate with a multi-channel approach spanning technical research communities (GitHub/arXiv/Hugging Face) and LinkedIn, plus access to founder networks like NVIDIA Inception. Has experience initiating cold founder relationships and progressing them through intro calls into deeper technical and business diligence, with a structured weekly pipeline/partner update cadence and thematic notes on frontier technologies.”

Daniel Benyamin

Screened

Executive AI and product leader specializing in media, advertising, and data platforms

Los Angeles, CA28y exp

“Serial entrepreneur in marketing and advertising who has founded four companies, most of them venture-backed. Has raised pre-seed and other venture funding multiple times, mentored at Techstars, and brings a strong investor network plus firsthand experience across the VC, accelerator, and launchpad ecosystem.”

Jeremiah Medina

Screened

Senior AI/ML Engineer specializing in LLMs, RAG, and cloud-native MLOps

Orlando, FL11y exp

“Built and owned a real-time clinical AI assistant at Andor Health, taking it from prototype through deployment, monitoring, and iterative improvement. Brings strong healthcare-focused GenAI experience across RAG, hybrid retrieval, LoRA fine-tuning, and production Python services, with measurable gains in accuracy, speed, and reliability.”

John Bralich

Screened

Senior Machine Learning Scientist specializing in generative AI and applied NLP

Juno Beach, FL9y exp

“ML/AI tech lead who shipped a production LLM workflow at GoDaddy for personalized marketing content, using rich customer context and human-plus-LLM evaluation to drive a statistically significant increase in customers creating posts with GoDaddy tools. Also has experience translating embedding research into a production government RFP search engine, with hands-on optimization of retrieval latency, model size, and deployment reliability.”

“Robotics software engineer with hands-on ROS2 experience building an audio conversion node and integrating Whisper LiveKit for streaming speech-to-text in a simulated hostile (outer space) robot environment. Also worked on a 2023 LiDAR + ML vision obstacle-detection project for a hospital-nurse-assistant robot, and has strong large-scale CI/CD deployment experience from AWS (2022–2024) across alpha/pre-prod/prod stages.”

“Robotics software engineer/researcher with hands-on experience building a MuJoCo-based digital twin of a 6DOF soft-actuated manipulator, spanning robot design, custom actuator dynamics, classical control (PID/MPC), and RL (imitation learning and TD-MPC2 model-based RL). Also has ROS1-in-Docker SLAM integration/visualization experience and delivered a major trajectory-tracking improvement (error reduced from ~100mm to ~5mm) via Savgol smoothing, plus prototype fleet communications work for a solar-powered power line inspection robot.”

“Senior data/AI and platform leader with Walmart- and T-Mobile-scale architecture experience, including building real-time inventory + forecasting platforms (Kafka/Cassandra/Hadoop) and Azure IoT systems. Known for translating board-level business goals into roadmaps that deliver measurable impact (e.g., $50M savings and $250M profit in a year; +2% conversion via Customer 360) and for hands-on problem solving in ML/forecasting (feature reduction and LASSO).”

Shahmeer Malik

Screened

Junior Software Development Engineer specializing in cloud security and CI/CD

Herndon, VA2y exp

“Backend/security-focused engineer supporting a service with 100k+ monthly users. Built an automated load-testing suite that reproduced and mitigated catastrophic host failures from oversized SCP/rsync transfers via host-level throttling, and proposed a future sharding approach for very large transfers. Also created an internal agent to summarize anomalous metrics and provide ready-to-run debug queries, significantly reducing ops review time.”

“Robotics software engineer with extensive ROS2 academic project experience (UMDCP), including a drone-based 3D object reconstruction system using Mast3r where they built ROS2 nodes for autonomous image capture, containerized the ROS2/OpenCV stack for hardware deployment, and automated AWS uploads/compute-triggered reconstruction. Demonstrated strong sim-to-real debugging using ROS bags and PlotJuggler to correct yaw/trajectory offsets, and built multi-node TurtleBot navigation using visual cues (horizon/stop signal/obstacle detection) feeding a cmd_vel controller.”

“Data science/NLP practitioner with experience at NVIDIA and Microsoft building production-grade NLP and data-linking systems. Has delivered high-performing pipelines (e.g., F1 0.92) and large-scale entity resolution (F1 0.89), plus semantic search using embeddings and Pinecone with ~30–40% relevance gains, backed by rigorous validation (A/B tests, ROUGE, MRR) and strong MLOps/workflow tooling (Airflow, Databricks, FastAPI, MLflow, Prometheus/ELK).”