Vetted Version Control Professionals

“Software/cloud engineer with PwC experience deploying a nationwide Australian Government Salesforce labor licensing platform used by 200k+ professionals, emphasizing safe integration, CI/CD, and UAT-driven quality improvements (40% defect reduction). Also built a Python/FastAPI RAG system with the U.S. Army to convert CONOP documents into risk assessments, adding human-in-the-loop and provenance features to address operator trust concerns.”

“Real-time character animation/tech art specialist spanning Maya rigging/auto-rigging through UE5 Animation Blueprints, Control Rig (FBIK/IK), and motion matching. Has shipped performance-focused work on an FPS targeting 60 FPS with 20+ AI and motion matching, using Unreal Insights, URO, PCA, and gameplay-tag pruning. Also collaborated on a VR brain-surgery simulation, translating desired vascular behavior into procedural Control Rig spring-based animation via rapid prototyping.”

“Robotics/computer-vision engineer with industrial safety monitoring experience, building real-time pose estimation (TRTPose) and 2D-to-3D localization and optimizing pipelines to sustain 30+ FPS under heavy multi-entity load. Also brings edge-to-cloud distributed systems work (HoloLens + Google Vision/Translation) and production ML deployment experience using Docker/CI/CD across finance and edge camera environments.”

Chetan Mukhopadhyay

Screened

Senior Engineering Manager specializing in software quality, automation, and web/mobile platforms

Seattle, WA16y exp

“Engineering leader at Bayer Crop Science leading a Core Platform team responsible for widely used open-source TypeScript/React and mobile SDKs (npm/GitHub) embedded across 10M+ monthly active devices. Known for shipping high-performance, backward-compatible developer frameworks with rigorous release discipline (bi-weekly releases, 99.99% uptime, long streaks of zero breaking changes) and major DX wins (onboarding cut to minutes, support tickets down 82%).”

“Postdoctoral/PhD researcher focused on Alzheimer's disease who has built scalable end-to-end AI systems across pathology imaging, transcriptomics, and longitudinal neuroimaging. Particularly strong in turning novel research ideas into robust Python pipelines on GPU/HPC infrastructure, with pathologist-facing impact and scientifically novel findings such as image-derived disease severity trajectories and subtype discovery.”

“IBM-based cloud and AI engineer with hands-on experience owning Azure deployment workflows end-to-end, including IaC, DevOps automation, and cost/performance optimization. Also built an edge-first hospital event-detection workflow combining vision, LLM orchestration, and privacy-preserving local processing in a Nvidia/Dell hackathon that won first place.”

“React-focused engineer who built a full-stack analytics/test-metrics dashboard (React frontend + Python backend) and turned common UI pieces (data tables, filter panels, chart wrappers) into a reusable internal component library with docs, examples, and basic tests. Strong on profiling-driven performance optimization (React Profiler, memoization) and on owning ambiguous internal-tool projects end-to-end; now planning to package internal patterns into public open-source components.”

“Corporate strategy / M&A professional with experience acting as a chief-of-staff-style associate to multiple managing directors at Focus Financial Partners while running parallel M&A, enterprise vendor negotiations, and infrastructure strategy work. At BNY, led strategic growth initiatives around fintech partnerships (TAM + financial modeling) and supported a confidential divestiture using rigorous information-control processes.”

“Robotics software engineer who built and owned an autonomous laparoscope tracking system on a UR3e with an eye-in-hand RealSense camera, integrating YOLO-based tool detection with velocity control under a strict RCM constraint and deploying successfully in a hospital setting. Deep ROS2/MoveIt2 experience (architecture, QoS, custom nodes) plus autonomy stack work across SLAM, planning, and real-time latency/control debugging.”

“ML/LLM engineer building production, real-time fraud detection for financial transactions using a two-tier architecture (fast ML + GPT) to deliver both low-latency decisions and analyst-friendly risk explanations. Experienced orchestrating end-to-end retraining, drift monitoring, and automated model promotion with Databricks Jobs/Workflows and MLflow, and partnering closely with fraud analysts to tune alerts, thresholds, and dashboards.”

“ML/LLM practitioner with production experience building a healthcare review sentiment pipeline (RateMDs) using Hugging Face Transformers plus a LangChain+FAISS RAG layer for interactive querying. Also led orchestration-driven optimization of Nike’s Fusion ETL pipeline, improving runtime efficiency by 20%, and has experience translating ML outputs into Tableau dashboards for non-technical healthcare stakeholders (e.g., readmission risk).”

“At Citi, helped lead the productionization of an internal LLM-driven automation workflow into a production-ready developer platform, focusing on determinism/reproducibility, security, and cost controls. Implemented prompt versioning/registry, JSON schema validation, sanitization, and deep telemetry (including manual edit-distance) plus human-in-the-loop review and phased rollout—driving major SDLC efficiency gains (e.g., test script creation cut from ~1 week to ~1 day).”