Headline

AI/ML Engineer @RankinSoft |Python| SQL| Machine Learning| Deep Learning| LLM| RAG| AWS| Docker|Kuberntes|Linux|Building Data-Driven and Forecasting Systems

About

AI/ML Engineer at RankinSoft | LLMs · RAG · Forecasting Systems At RankinSoft, I design and deploy end-to-end machine learning solutions — spanning LLM applications, retrieval-augmented generation (RAG) systems, and data-driven forecasting pipelines built for scale. Core expertise: Python · SQL · Machine Learning · Deep Learning · AWS · Docker · Kubernetes · Linux Focused on bridging the gap between ML research and production engineering — building systems that are not just accurate, but reliable and deployable at scale. Open to connecting with engineers, researchers, and teams pushing the boundaries of applied AI.

Location

Bengaluru

AI stack

anthropic apis

antigravity

claude code

codex

cursor

gemini

Work experience

AI/ML Engineer at Rankinsoft, May 2026 - Present · 4 mos, San Francisco, California, United States, I'm an AI/ML Engineer at RankinSoft, where I design and deploy intelligent, production-ready machine learning systems that solve real-world problems at scale. My core work spans the full ML lifecycle — from data engineering and model development to cloud deployment and monitoring. I specialize in building LLM-powered applications, retrieval-augmented generation (RAG) pipelines, and data-driven forecasting systems that translate directly into measurable business outcomes. At RankinSoft, I work at the intersection of research and engineering — taking ideas from experimentation to production using modern MLOps practices on AWS, containerized with Docker and orchestrated via Kubernetes. What I bring to every project: Deep expertise in Python and SQL for data pipelines and feature engineering Machine learning and deep learning model development and optimization LLM fine-tuning, prompt engineering, and RAG system design Cloud-native deployment on AWS with Docker and Kubernetes Linux-based development and infrastructure management I'm passionate about building systems that don't just work in notebooks — but scale, perform, and deliver value in production. Open to connecting with engineers, researchers, and teams building the future of applied AI.

ML operations at Amazon, Jun 2025 - May 2026 · 1 yr, Bengaluru, Karnataka, India, Experience — Amazon ML Operations Engineer Supported and optimized machine learning workflows within Amazon's large-scale cloud infrastructure, ensuring reliable model deployment, monitoring, and performance across production environments. Managed end-to-end MLOps pipelines on AWS, overseeing model versioning, deployment automation, and continuous integration for ML systems Monitored deployed models for performance degradation, data drift, and latency issues, triggering retraining workflows to maintain prediction quality at scale Collaborated with data scientists and software engineers to bridge the gap between model development and production deployment Leveraged AWS services including SageMaker, S3, EC2, Lambda, and CloudWatch to build and maintain robust, scalable ML infrastructure Implemented containerized model serving using Docker and Kubernetes, improving deployment consistency and reducing time-to-production Contributed to automating data pipelines and feature engineering workflows, reducing manual overhead and improving model refresh cycles Ensured system reliability, uptime, and compliance with internal SLAs across multiple ML products and teams

MLOps Engineer at Microline informatiion systems, Jan 2024 - Apr 2025 · 1 y 3 mo, Hyderabad

Education

Bachelor of Engineering - BE, Artificial Intelligence, Parul University

Intermediate MPC, Narayana Junior College - India