Vetted C++ Professionals

“Data engineer focused on large-scale ETL/ELT pipelines across cloud stacks (GCP and AWS), including Spark-based transformations and orchestration with Airflow. Has experience loading up to ~2TB per BigQuery target table and designing atomic loads to multiple downstream systems (Elasticsearch + Kafka), with Kubernetes deployment and Jenkins CI/CD.”

“Robotics/ML engineer (Stanford project) who built a full Python-based RL grasping pipeline for an anthropomorphic tactile hand in MuJoCo, implementing SAC + behavioral cloning and proposing curriculum experiments; second author on an ICRCA 2026 submission. Hands-on with ROS 2 integration for Flexiv Rizon 4 and LEAP Hand, and uses Docker/Distrobox to manage complex CUDA/OS constraints while running training and production-style inference/retraining workflows.”

“Robotics software engineer focused on ROS2 motion and calibration systems—built a trajectory generator/low-level controller using TOPPRA that improved robot motion speed by 11x while increasing accuracy. Experienced making high-frequency robot communication more real-time (core isolation) and shipping ROS2 modules via Docker-backed CI/CD, including serving as release manager coordinating reviews, release notes, and QA.”

“Robotics technical lead who architected and built a high-speed autonomous lunar rover mobility software system for GPS-denied environments, integrating MPC/LQR control, trajectory optimization, state and slip estimation, terrain-aware planning, and perception. Has deployed Deep RL policies trained in NVIDIA Isaac Sim onto real rover hardware via a ROS2 inference-node interface, with strong focus on real-time performance profiling, sim-to-real, and safety/HIL testing.”

“Master’s student at UC San Diego who built an LLM-powered healthcare chatbot for patient history-taking and sepsis-related output, using a Node.js backend integrated with FastAPI for RAG/LLM interactions and a Flutter client. Also has healthcare AI startup experience deploying on AWS (ECS/Terraform/Docker) and implementing Kubernetes autoscaling to improve efficiency and reduce costs, with strong iterative evaluation in collaboration with a physician.”

“Built and deployed an in-house RAG LLM system ("MONTY") using LLaMA 3B + FAISS to help teams quickly understand long internal/external specifications. Delivered usable production performance despite severe compute limits (single RTX 3080) by tuning retrieval/reranking and model choice, and is planning a LightRAG/knowledge-graph rewrite to improve accuracy and latency.”

“Solutions engineer at a Voice AI startup building and deploying voice agents for self-storage customers, owning the full lifecycle from cold outreach and demos through contract negotiation, FMS/API integration, and post-sales optimization. Also has Audi/Porsche experience demoing pre-production vehicles and autonomous driving features (L3 lane changes) to internal stakeholders and VW Group leadership, with a strong track record of tailoring technical narratives to varied audiences and improving conversion by adapting agents to regional dialects.”

“Ticketmaster data engineer who built CDC-driven Kafka pipelines feeding Snowflake for analytics and data science teams. Hands-on in production operations—scaled Kafka during sudden playoff-driven transaction spikes and improved monitoring for preemptive scaling. Known for using small-batch experiments and quantitative metrics to align stakeholders and drive cost-saving architecture changes (e.g., buffering to reduce AWS Lambda invocation frequency).”

“Backend engineer with experience at UnitedHealth Group redesigning a high-traffic Spring Boot microservice from blocking to reactive architecture during peak season, cutting median latency by 47% for a service used by ~10M customers annually. Strong in Kubernetes-based deployment/scaling and pragmatic rollout strategies (blue-green/incremental traffic shifting) with performance and database troubleshooting.”

“Teradata Text Security intern who built a production LLM-powered planner agent that decomposes complex tasks into dependency-aware subtasks (DAG/topological graph) and executes them via a custom orchestrator with parallelism, status tracking, and error handling. Also contributed to an HR-facing internal document chatbot concept to streamline onboarding, showing cross-functional collaboration.”

“Robotics software engineer focused on vision-guided manipulation with a Franka Emika Panda on ROS 2, using an RGB-D camera and a trained YOLO-OBB detector to estimate 3D object poses for pick-and-place. Strong in perception-to-planning integration (TF2 alignment, message synchronization, MoveIt 2) and in debugging sim-to-real issues, including symmetry-aware orientation handling and grasp repeatability tuning.”

“Backend engineer who built a real-time pipeline for recording, transcribing, and analyzing audio from 400+ news radio stations, scaling Whisper on an HPC cluster with 7 H100 GPUs. Has strong performance optimization experience (30% latency reduction via SQL/query design; 50% DB call reduction via Redis caching) and has implemented region-based data isolation and PII protections in a regulated environment (JP Morgan Chase).”

“Robotics software engineer who built a targeting/payload delivery module for an FPV drone, integrating GNSS/IMU and other sensors with an EKF-based fusion stack and multi-rate synchronization. Also designed a servo gimbal with a laser ToF sensor to validate predicted landing locations using DH-based forward/inverse kinematics, leveraging ROS2/Gazebo for simulation and Python/MATLAB for filter tuning.”

“Backend engineer with experience at Amazon building an API-driven service (APS) for large-scale prompt optimization jobs using AWS Step Functions, Batch/Fargate, DynamoDB, and S3, emphasizing idempotency, observability, and secure execution boundaries. Also led a multi-tenant enterprise policy/configuration backend refactor at MAMIT Cyber with versioned schemas, shadow writes, feature-flagged rollout, and PostgreSQL RLS-based tenant isolation.”

“ML/AI engineer focused on production-grade model reliability: built a monitoring and validation framework to detect drift, trigger anomaly alerts/retraining, and maintain consistent performance for device intelligence workflows at scale. Strong MLOps background with Python pipelines, Docker/Kubernetes deployments, Airflow orchestration, and real-time monitoring dashboards; experienced partnering with product managers to deliver business-facing insights.”

“Qualcomm engineer building Android applications that run on Qualcomm AI accelerators, with hands-on experience in C++ concurrency, chipset stress testing, and power/performance tuning. Has deployed on-device AI models and built deployment/log post-processing workflows using Docker/Kubernetes and CI/CD; interested in translating this embedded AI/performance background into robotics (perception/real-time systems).”

“Robotics/ML engineer with hands-on experience building multimodal waypoint prediction for autonomous driving using CLIP + LidarCLIP embeddings and PyTorch, including nuScenes data pipelines and baseline modeling. Also built ROS 2 nodes for TurtleBot maze navigation with an image-classification pipeline, and has Caterpillar experience doing dSPACE HIL testing with MATLAB/Simulink plant models for engine software validation.”

“SRE-focused engineer with experience at Sony Interactive Entertainment productionizing high-throughput LLM/agentic systems on Kubernetes, including GPU-aware autoscaling and warm-pool strategies to manage latency and cost under traffic spikes. Demonstrates strong incident response using Prometheus/Grafana + Jaeger tracing (e.g., resolving recursive agent loops and restoring 99.9% availability within minutes) and partners closely with sales/customer teams through PoV demos and developer workshops.”

“Robotics software engineer focused on outdoor mobile robot localization and navigation, building ROS1/ROS2 systems with NavSat+EKF sensor fusion and custom Nav2/Costmap2D extensions for 3D obstacle clearance. Demonstrates strong real-world troubleshooting by tracing localization drift to a failing IMU connector, repairing it, and then creating sensor-health monitoring tooling; experienced taking features from Gazebo simulation through field testing to Docker/Kubernetes deployment with CI via GitHub Actions.”

“Backend engineer from Palantir who built and productionized an enterprise LLM-based document intelligence/search platform, evolving it into a hybrid lexical+vector retrieval system. Emphasizes reliability and cost control via strict LLM gating, robust fallback paths, and evaluation frameworks (e.g., MMLU/BLEU), plus disciplined migration practices (feature flags, dual-writes, shadow reads) to ship changes safely at scale.”

“Robotics software engineer with extensive ROS2 experience building and integrating full autonomous navigation stacks (sensor fusion, ICP/occupancy-grid mapping, planning). Hands-on computer vision work for drones, including monocular depth-from-RGB pipelines (Open3D/OpenCV) and model swaps to improve low-light performance. Also experienced in multi-drone coordination with Crazyswarm2 and Vicon-based state estimation, plus Gazebo simulation for TurtleBot, Franka Emika, and a Lunabotics-style excavation rover.”

“Built and shipped a production multi-agent, voice-based conversational assistant for older adults’ daily health management using Vertex AI, FastAPI, Firebase/Firestore, and Cloud Run, with a custom cross-session memory design to keep responses context-aware at low latency. Also partnered with caregivers/elderly users and health officials, translating needs into workflows and explaining HIV risk predictions with SHAP and dashboards.”

“AI engineer at Anote.ai who built and shipped a production multi-agent LangGraph/LangChain/Ray RAG platform for enterprise search and workflow automation, supporting 3 commercial products and 100+ developers. Drove measurable gains (30% accuracy improvement, lower latency) and improved reliability with Redis-based state checkpointing, message-queue synchronization, and Milvus retrieval optimizations, while partnering with PMs/clients to add transparency features like confidence scores and real-time logs.”

“Full-stack engineer with experience at HubSpot, Accolite, and an early-stage USC alumni startup (Workup). Built and shipped end-to-end workflow automation features (dynamic input configuration with strict schema validation) driving ~25% faster configuration, and delivered an AI interview customization feature in a high-ambiguity startup setting that increased adoption by ~40%. Comfortable operating production systems on AWS with CloudWatch observability and CI/CD, and has built real-time web apps with caching/indexing for performance.”