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Vetted Flask Professionals
Pre-screened and vetted.
Mid-level Software Engineer specializing in distributed systems and FinTech
Mid-level Software Engineer specializing in distributed backend systems for FinTech
Mid-level Full-Stack Engineer specializing in cloud-native enterprise and FinTech systems
Senior Full-Stack AI Engineer specializing in AI products and developer platforms
Mid-level Full-Stack Developer specializing in Python, microservices, and AI platforms
Intern Software Engineer specializing in full-stack and computer vision
Senior Full-Stack Engineer specializing in compliance, integrations, and data platforms
Mid-level Frontend Engineer specializing in React and web applications
Senior Full-Stack Python Developer specializing in Django, FastAPI, and cloud platforms
Mid-level AI Engineer specializing in production LLM, RAG, and agentic AI systems
Senior Data Scientist specializing in NLP, MLOps, and cloud ML platforms
Senior AI Python Engineer specializing in Generative AI and MLOps
Senior Full-Stack Developer specializing in cloud microservices and enterprise applications
Harshini Kanamathareddy
Mid Software Engineer specializing in iOS, backend systems, and AI-powered applications
“Full-stack/backend engineer with experience spanning React/TypeScript, Flask, Spring Boot, SQL databases, and production mobile optimization. They’ve shipped features end to end, improved query performance and app startup/crash metrics, and helped drive a configuration-driven architecture that enabled faster releases across 30 consumer applications.”
Prayasha Chaudhary
Senior Engineering Leader specializing in cloud architecture and AI-powered data platforms
“Hands-on startup operator with experience across three startups, including companies built from inception and a PEAK6-backed environment. Particularly compelling for early-stage roles: they have rebuilt technical foundations, scaled platforms during growth, and pair strong product ownership with a practical, user-validation-first approach to building scalable systems.”
Swaraj Bhalerao
Mid-level Full-Stack Developer specializing in backend-heavy web applications
“Backend/full-stack engineer who has built AI-powered search and workflow systems in production, including a semantic resume-matching platform for recruiters and internal security data dashboards at ReliaQuest. Stands out for combining modern AI tooling with pragmatic reliability, performance tuning, and strong product intuition in ambiguous environments.”
Kristin Blier
Senior Geospatial Software Engineer specializing in 3D simulation environments
“Geospatial/simulation specialist who built and shipped high-fidelity 3D visual databases for a DoD-used simulation/render engine, owning the full pipeline from dataset selection and ingestion (imagery/LiDAR/OSM/elevation) through performance testing and delivery. Implemented Python-based AI scripts to auto-detect terrain features and drive automated 3D scene population, and has experience with authoritative client-server synchronization (DIS) plus VR headset performance constraints (Varjo/Oculus/HoloLens at 90Hz).”
Chris Harry Patrick
Mid-level AI/ML Engineer specializing in healthcare, risk modeling, and MLOps
“Robotics software engineer who built a ROS Noetic-based perception-to-control stack for a pick-and-place robotic arm, integrating OpenCV/TensorFlow vision with motion planning and PID tuning. Demonstrated strong real-time debugging skills (rosbag, queue/latency fixes) and experience deploying reproducible robotics environments with Gazebo simulation, Docker, and GitLab CI.”
Ujwal Waghray
Mid-level Robotics & Software Engineer specializing in ROS 2 autonomy and ML
“Master’s-level IoT course project that the candidate helped evolve into a research lab effort by “ROSifying” a soil-fertility detection rover (autonomous navigation within a GPS geofence, sensor fusion, and rover-to-base-station telemetry via NRF24 to a Raspberry Pi dashboard). Also built a ROS/Gazebo vision-based teleoperation system using a SigLIP hand-gesture model mapped to geometry_msgs/Twist, and improved stability by instrumenting and filtering a latency-prone perception-to-control pipeline.”