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Soma Meghana Prathipati
Mid-level Machine Learning Engineer specializing in NLP, federated learning, and fraud detection
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About
ML/robotics engineer with Apple experience who built a computer-vision-driven industrial defect detection system integrating a robotic arm with ROS-based real-time inference on an edge GPU. Drove major performance gains (cut inference time ~60% via quantization + TensorRT) and improved robustness to lighting/material variation, with strong emphasis on production reliability (health checks, watchdogs, observability, CI/CD) and interest in shaping early-stage startup engineering culture.
Experience
Education
Key Strengths
- End-to-end build of real-time vision + robotics defect detection system (data collection through deployment)
- Inference latency optimization via quantization + TensorRT (reduced inference time ~60%)
- ROS-based real-time integration between vision, inference, and robotic control (publisher/subscriber, actionlib)
- Production reliability engineering: profiling end-to-end latency, asynchronous callbacks, watchdog timers, health checks
- Robustness to domain variability (lighting/material texture) using adaptive preprocessing and augmentation
- Edge deployment and containerization for low-latency pipelines (Docker on edge GPU)
- Scalability mindset informed by Apple experience (early profiling, iterative optimization, resilience checks)
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