Vetted Deep Learning Professionals

“Built Cigna Health’s risk-based management/monitoring system used as a primary product for pharmaceutical clients, supporting clinical trials and utilized during the COVID-19 pandemic. Currently running a community-based startup (details kept proprietary) and is open to executive roles or joining a strong team with a clear path to success, evaluating opportunities via ROI.”

“Robotics software engineer with hands-on experience building autonomy features across perception, planning, and systems integration—most notably for an autonomous lunar rover that detects and geometrically models craters to plan terrain manipulation. Also owned development of an autonomous stair-climbing module for a quadruped robot as an intern, and has real-time motion-planning/IK debugging experience on a Franka Panda using RGB-D (RealSense).”

“PhD (CS) candidate with hands-on autonomy and robotics experience: improved safety-critical behavior for Kodiak’s self-driving 18-wheeler trucks, increasing overtaking clearance by ~2 feet and reducing safety alerts. Also debugged a C++ SLAM system for 3D colon reconstruction and built a low-budget distributed simulation cluster using Linux, Docker, and Python, plus implemented multi-hop SSH-based comms for an underwater robotics competition minibot.”

“AI engineer building and deploying deep-learning-based optimization/control systems for petrochemical plants, with a focus on maintaining operational stability under real-world constraints. Core contributor to model and inference design; introduced a stability-focused non-linear objective and sped up second-layer optimization via on-the-fly first-order approximations. Experienced using Kubernetes for end-to-end testing and effective in translating customer expectations into measurable evaluation plots for non-technical stakeholders.”

“ML/LLM practitioner with experience at Truveta building an LLM-based evaluation framework; identified non-overlapping evaluator failure modes and proposed an ensemble approach that enabled scaling training data and drove ~5% performance gains across multiple internal projects. Strong focus on robustness to distribution shift (augmentation/domain adaptation/meta-learning) and production reliability via monitoring, drift detection, and safe fallbacks.”

“Applied ML/LLM practitioner working in healthcare-facing products, using RAG and LoRA fine-tuning on medical data and implementing production monitoring (confidence scoring) for clinician oversight. Has hands-on experience debugging agentic/LLM pipelines (including OCR preprocessing fixes) and regularly delivers technical demos to doctors, investors, and conferences—contributing to adoption and even helping close a funding round through end-to-end pipeline walkthroughs.”

“Backend engineer with deep experience building event-driven logistics systems (orders, warehouse execution, real-time delivery tracking) using Spring Boot/PostgreSQL/Redis and strong observability (Prometheus/Grafana). Led a zero-downtime migration from monolithic MySQL to a sharded architecture for ~2M users with dual-write, checksum validation, and fast auto-rollback, and has strong security expertise including PostgreSQL RLS for multi-tenant SaaS and robust OAuth/JWT handling.”

“Built and deployed a live LLM-powered platform that takes a LinkedIn job URL + resume and generates job-specific resumes and personalized outreach at scale, with production-grade logging/monitoring/retries on Vercel + Railway. Experienced with agent orchestration (AWS Bedrock/Strands, LangGraph, CrewAI) and rigorous AI workflow testing, plus stakeholder-facing prototypes like data lineage/metadata and NL-to-SQL + dashboard generation.”

“Built and productionized LLM-driven sentiment scoring for earnings call transcripts at Goldman Sachs, replacing legacy NLP to deliver a cleaner trading signal while managing latency/cost via batching, caching, and distilled models. Also implemented an Airflow-orchestrated fraud modeling pipeline at MetLife with drift-based retraining and SageMaker deployment, and has a disciplined evaluation/rollout framework for reliable AI workflows.”

“Robotics software engineer leading an autonomy stack migration from ROS1 to ROS2, including a custom-built global parameter server to preserve existing infrastructure while shipping continuous production releases. Hands-on across navigation/safety/monitoring packages, control (ROS2 PID for steering/speed), and localization performance work (particle filter optimization), with strong ownership of CI-driven test strategy and release quality.”