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Hi, I’m Sahil Sharma, an AI Engineer with a Master’s in Data Science and production-grade experience at Mercedes-Benz AG. I specialize in building scalable RAG pipelines, multi-agent systems, and MLOps workflows on Azure and AWS. I’ve proven my ability to reduce manual operational effort by around 75% through intelligent automation, and I’m passionate about creating secure, impactful real-world solutions. In addition to my core work, I enjoy turning complex data into usable insights, collaborating across data science, software engineering, and product teams, and continuously learning new tools to drive faster, higher-quality outcomes. I’m excited to contribute to teams developing scalable AI-powered systems.…Hi, I’m Sahil Sharma, an AI Engineer with a Master’s in Data Science and production-grade experience at Mercedes-Benz AG. I specialize in building scalable RAG pipelines, multi-agent systems, and MLOps workflows on Azure and AWS. I’ve proven my ability to reduce manual operational effort by around 75% through intelligent automation, and I’m passionate about creating secure, impactful real-world solutions. In addition to my core work, I enjoy turning complex data into usable insights, collaborating across data science, software engineering, and product teams, and continuously learning new tools to drive faster, higher-quality outcomes. I’m excited to contribute to teams developing scalable AI-powered systems.

Sahil Sharma

AI Engineer, Data Scientist, Data Analyst, +4

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Hi, I’m Sahil Sharma, an AI Engineer with a Master’s in Data Science and production-grade experience at Mercedes-Benz AG. I specialize in building scalable RAG pipelines, multi-agent systems, and MLOps workflows on Azure and AWS. I’ve proven my ability to reduce manual operational effort by around 75% through intelligent automation, and I’m passionate about creating secure, impactful real-world solutions. In addition to my core work, I enjoy turning complex data into usable insights, collaborating across data science, software engineering, and product teams, and continuously learning new tools to drive faster, higher-quality outcomes. I’m excited to contribute to teams developing scalable AI-powered systems.…Hi, I’m Sahil Sharma, an AI Engineer with a Master’s in Data Science and production-grade experience at Mercedes-Benz AG. I specialize in building scalable RAG pipelines, multi-agent systems, and MLOps workflows on Azure and AWS. I’ve proven my ability to reduce manual operational effort by around 75% through intelligent automation, and I’m passionate about creating secure, impactful real-world solutions. In addition to my core work, I enjoy turning complex data into usable insights, collaborating across data science, software engineering, and product teams, and continuously learning new tools to drive faster, higher-quality outcomes. I’m excited to contribute to teams developing scalable AI-powered systems.

Available to hire

Hi, I’m Sahil Sharma, an AI Engineer with a Master’s in Data Science and production-grade experience at Mercedes-Benz AG. I specialize in building scalable RAG pipelines, multi-agent systems, and MLOps workflows on Azure and AWS. I’ve proven my ability to reduce manual operational effort by around 75% through intelligent automation, and I’m passionate about creating secure, impactful real-world solutions.

In addition to my core work, I enjoy turning complex data into usable insights, collaborating across data science, software engineering, and product teams, and continuously learning new tools to drive faster, higher-quality outcomes. I’m excited to contribute to teams developing scalable AI-powered systems.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

German

Fluent

English

Fluent

Work Experience

Generative AI and Data Science Intern at Mercedes-Benz AG

May 1, 2025 - Present

Developed production-ready image generation and upscaling pipelines for the Marketing team; designed and deployed FastAPI endpoints to expose these pipelines as scalable RESTful services on Azure Web Apps; built ComfyUI workflows with Stable Diffusion models to generate background images for marketing campaigns; developed a multi-agent system with Google Agent Development Kit and MCP/A2A protocols to assist board members in speech enrichment across formats; fine-tuned open- and closed-source models on executives' LinkedIn and speech data to adapt to ontology and writing style; participated in Scrum-based Agile development with sprint planning and daily stand-ups.

Generative AI and Data Science Intern at Mercedes-Benz AG

May 1, 2025 - Present

Developed production-ready image generation and upscaling pipelines for the Marketing team; designed FastAPI endpoints to expose pipelines as scalable RESTful services on Azure Web Apps; built multi-modal content workflows with Stable Diffusion for marketing campaigns; implemented a multi-agent system using Google Agent Development Kit and MCP/AP protocols to assist leadership in speech enrichment across formats; fine-tuned open-source models on executive LinkedIn data to tailor outputs; contributed to Scrum-based Agile development with sprint planning and daily stand-ups; evaluated pipeline performance on a 50-question German-English Q&A dataset, achieving a 4.8/5 average; built a Docker image and deployed a chatbot with a React-based web interface on the university server for testing and validation.

Generative AI and Data Science Intern at Mercedes-Benz AG

October 1, 2025 - October 1, 2025

Built production-ready image generation and upscaling pipelines with Stable Diffusion to improve content quality for Mercedes-Benz Marketing campaigns. Deployed pipelines as scalable FastAPI RESTful services on Azure Web Apps for seamless workflow integration. Contributed to developing a multi-agent system using Google Agent Development Kit and MCP/A2 protocols to assist board members with speech enrichment. Fine-tuned models on executive LinkedIn and speech data to generate personalized content with adapted tonality.

End-to-End Waste Classifier (CI/CD on AWS) at Self-initiated project, Erlangen

November 1, 2025 - November 1, 2025

Built an end-to-end waste-classification system using EfficientNetV2B1 with 98% accuracy, delivering real-time image predictions through a FastAPI backend and React frontend. Containerized and deployed the platform on AWS ECS (Fargate) using ECR, Nginx, and an Application Load Balancer for scalable, production-grade serving. Implemented CI/CD pipelines with GitHub Actions and Terraform to automate testing and infrastructure deployments.

Panoptic Segmentation on Dendrites and Dendritic Spines at Erlangen Institute / Lab

July 1, 2024 - July 1, 2024

Designed a panoptic segmentation pipeline to detect and differentiate dendrites and dendritic spines using FCN-ResNet and Mask R-CNN architectures. Converted binary masks of dendrites into instance masks using scikit-image to enable instance-level segmentation. Achieved IoU ~88% on evaluated datasets.

Route Navigation System for the Visually Impaired at Sensation Project, Erlangen

March 1, 2024 - March 1, 2024

Developed a route navigation system for visually impaired individuals as part of the Sensation project, enhancing mobility and safety. Trained and fine-tuned a semi-automatic model on Cityscapes and Mapillary datasets, improving sidewalk detection accuracy by 30%. Evaluated system performance on real-world route videos, achieving IoU 82% with high-precision results.

Master's Thesis at Friedrich Alexander University (FAU) Erlangen-Nuremberg

February 1, 2025 - February 1, 2025

Master's Thesis: Enhancing Knowledge Extraction from Domain-Specific Documents.

AI Engineer Intern at Mercedes-Benz AG

May 1, 2025 - October 1, 2025

Engineered and deployed scalable image generation and upscaling pipelines using Stable Diffusion and FastAPI on Azure Web Apps, improving visual asset quality for global marketing campaigns. Automated workflow orchestration using Databricks jobs, ensuring seamless data handover between generation and serving layers. Developed a board-level assistant using Google Agent Development Kit (ADK); fine-tuned LLMs on executive speech data to automate personalized content generation with >85% tonal accuracy.