Professional Overview
AI Algorithm Engineer with 3+ years of experience designing, deploying, and optimizing production-grade Computer Vision and Generative AI solutions. Experienced in DeepStream, CUDA, Triton Inference Server, Docker, PyTorch, YOLO, RAG, and LLM integration for large-scale video analytics. Led end-to-end AI deployments across cloud and edge.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Led enterprise AI deployments for Latin America projects and Lucknow Smart City
- Mentored 3–4 AI engineers and supported deployments across edge and cloud
- Designed GPU-accelerated AI pipelines using NVIDIA DeepStream, CUDA, TensorRT,
- ... Triton Inference Server, Docker and ONNX.
- Documented AI deployment procedures.
Key Achievements / KPIs
- Improved production stability by refactoring inference pipelines and using DS ..
- .. solely for inference, eliminating recurring server restart issues.
- Delivered production Computer Vision systems supporting approximately 800 CCTV
- .. cameras across three GPU inference servers.
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
