Vetted Python Professionals

“AI/LLM practitioner who built a GPT-2-like language model from scratch at the University of Maryland using PyTorch and multi-GPU distributed training, with experiment tracking in Weights & Biases. As an AI Operations intern at ScaleUp360, delivered multiple production-style AI agent automations (Gmail classification and Fireflies-to-Claude workflows that extract and assign CEO tasks) and set up measurable evaluation using test cases and classification metrics.”

“Recent graduate with a prototyping/hardware engineering background who is building a ROS2-dependent swarm robotics system for transporting non-standard cargo using 3+ robots. Has hands-on experience integrating multiple sensor modalities (LiDAR, IMU, GPS, radar) and developing custom teleoperation ROS nodes, currently tackling networking/communication challenges in multi-robot coordination.”

“Backend engineer who built Flask-based internal APIs supporting GenAI-driven provisioning/diagnostics (Outpost/AWS Outposts-like environment), with deep hands-on optimization across Postgres/SQLAlchemy (2s to <200ms endpoint improvement). Experienced integrating ML/LLM workflows via AWS SageMaker and Bedrock, and designing multi-tenant isolation plus high-throughput Redis-backed background task pipelines (minutes to seconds).”

“IoT/connected-device and SaaS product builder with deep connected health/telehealth experience, including patient care delivery and remote patient monitoring. In their current org, they expanded a nutrition product business by prototyping and piloting a digital pre/post-surgical coaching care-delivery service with real providers/clinics/patients, then building an MVP and taking it to market.”

“ML-focused candidate with beginner ROS/ROS2 experience (custom pub-sub nodes; TurtleBot3 SLAM simulation debugging via topic inspection and transform/orientation checks). Has research/project exposure to LLM training approaches (GRPO with pseudo-labels using Hugging Face TRL on Qwen/Llama) and uses Docker/Kubernetes + CI/CD to run ViT saliency-attention/compression workloads on UCSD Nautilus infrastructure.”

“Robotics software engineer (10+ years ROS/ROS 2) currently leading the perception stack for Omron’s AMR fleet, including a scalable factory SLAM system that combines vision with laser SLAM to handle corridor aliasing. Strong in real-time embedded optimization on NVIDIA Jetson (CUDA + profiling) and fleet-scale validation via multi-robot Isaac Sim scenarios (USD-to-ROS 2 bridging, Nav2 in crowded scenes). Also contributed to a cloud-native reality-capture/3D reconstruction pipeline at Hilti using Docker and Kubernetes.”

“Built and shipped a map-embedding SDK (published to npm) for Walmart apps, solving key performance issues with real-time streaming (WebSockets) and Canvas rendering while prioritizing developer experience. Also applies LLM/agentic patterns in production workflows—using diagnostic agents and human-in-the-loop escalation to detect and resolve issues (e.g., voice agent loops caused by RAG API failures). Has sales-engineering experience supporting enterprise renewals, including a million-dollar contract renewal while at Siemens working with Ford stakeholders.”

“Full-stack engineer with experience at Zoho and Amazon who has owned production systems end-to-end, including a monolith-to-microservices migration using Kafka and Cassandra that improved search latency ~25% and increased throughput without data loss. Also built a hackathon project (Buildwise) into a sold product for a construction company (AI-driven document compliance checks) and shipped an IoT-based parking availability MVP in 3 weeks.”

“Robotics software engineer working on an electric seaglider autonomy/perception stack on NVIDIA Orin, tackling multi-modal operating constraints (5–10 knots float mode up to ~100 knots flight). Previously built a ROS-based multi-robot search-and-rescue system, including navigation integrated with SLAM/task allocation/perception, and improved real-world performance by switching to a 2D planner with a velocity-obstacles controller to handle slip and timing uncertainty.”

“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”

“Backend engineer who built a low-latency real-time transaction API in Python/Flask, with strong depth in PostgreSQL/SQLAlchemy performance tuning (time-based partitioning, indexing, connection pooling). Has production experience integrating ML scoring and OpenAI-style APIs with safety/latency controls, and designing multi-tenant isolation strategies including per-tenant pooling/caching and premium-tenant isolation.”

“Outbound-focused sales/business development experience at early-stage OneCo, owning end-to-end prospecting from lead list building and account research through cold email/LinkedIn sequences, booking first conversations, and handing off qualified leads. Leverages Clay, n8n, and AI tools to automate enrichment and speed research while keeping outreach highly personalized and concise.”

“CTO-level technology leader with experience building end-to-end tech strategy and roadmaps, modernizing legacy environments in healthcare (GenesisCare), and scaling engineering into large global teams (Amadeus). Built a DevOps organization at Syniverse for the Visibility Suite, implementing Kubernetes/Terraform/Chef automation that drove ~75% faster deployments, and is known for staying hands-on (including data center work) while leading strategically.”

“Backend-leaning full-stack engineer with experience at Liberty Mutual and Airbnb, building high-scale insurance claims systems (1M+ monthly transactions) and consumer booking/pricing services (120K–180K daily requests). Strong in transactional data integrity, PostgreSQL performance tuning, and production operations (Docker/Jenkins/AWS), with measurable UX/performance wins including ~2.3s page loads and significant runtime failure reduction.”