As a dedicated AI/ML and Generative AI engineer, driven by innovation and practical problem-solving, my focus is on building production-ready, scalable AI systems that deliver measurable business impact. With 9+ years of hands-on experience, my core expertise spans Data Science, Machine Learning, MLOps, and GenAI, including LLM-based applications, RAG pipelines, vector databases, predictive modeling, and end-to-end AI deployment.

I thrive on working across the complete AI lifecycle, from data processing, feature engineering, and model training to model evaluation, deployment, monitoring, and optimization in production environments. I regularly work with technologies such as Python, PyTorch, Hugging Face, LangChain, ElasticSearch, vector search systems, Docker, Kubernetes, and cloud platforms to bring AI-driven solutions into real-world use.

Alongside my AI-focused work, I bring strong full-stack engineering experience, enabling seamless integration of AI and ML models into scalable web applications and APIs. I have built and maintained backend systems using Django, MEAN, MERN, MongoDB, and modern frontend frameworks, allowing me to take ownership from model development to production-grade applications.

Beyond technical execution, I value clear communication and collaboration as key drivers of successful outcomes. By actively engaging stakeholders throughout the development lifecycle, I ensure solutions are aligned with both technical feasibility and business objectives.

My commitment to continuous learning keeps me actively involved in industry communities, academic initiatives, and open-source projects, where I explore emerging AI technologies and contribute to shared innovation.

Let’s work together to create AI-driven solutions that make a real difference.