RISHABH SRIVASTAVA

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Assessing your cultural and operational fit

• Exceptional technical proficiency and extensive experience (7+ years) in Machine Learning, Deep Learning, and Computer Vision, making the candidate a strong match for a Python Engineer role with an ML/DL focus.
• Comprehensive understanding and hands-on experience across the entire ML lifecycle, including model training (YOLO, REIDnet, CNNs, Vision Transformers, LLMs like Qwen), data augmentation (TrafficSignGAN, Stable Diffusion), deployment (Deepstream, Triton Inference Server, TensorFlow Lite, NCNN, OpenVINO), and MLOps (MLFlow, Docker, Kubernetes, CI/CD).
• Strong backend development skills with Python (FastAPI, Flask), Java (Spring Boot), Node.js, and C++ for performance-critical components, demonstrating versatility in building robust systems.
• Deep expertise in cloud platforms (AWS EC2, S3, EKS, Elastic Beanstalk) and containerization (Docker, Kubernetes), essential for modern scalable ML deployments.
• Proven experience with real-time data processing and streaming technologies (Kafka, WebRTC, WebSockets, Socket.IO, MQTT), crucial for real-time analytics and ADAS systems.
• Proficient with modern AI tools including vector databases (PGvector, Milvus, FAISS) and LLM frameworks (LangChain, LangGraph, OpenAI SDK), showcasing up-to-date skills in generative AI and semantic search.
• Demonstrated ability to work with embedded systems (NVIDIA Jetson Nano) and optimize models for edge computing environments, indicating practical deployment capabilities in constrained hardware.