Hannover-Braunschweig-Göttingen-Wolfsburg Region
Hands-on AI Architect specializing in the next generation of autonomous compute. Currently building a core AI operating system from scratch at an early-stage startup in stealth mode. My work focuses on designing multi-agent orchestration frameworks that solve complex, multi-step reasoning problems for deep tech, high-tech manufacturing, and enterprise verticals. Expert in bridging hardware-level constraints with advanced AI agent architectures, vector infrastructure, and scalable system design. At videantis GmbH, my role as a Deep Learning AI Engineer intertwines advanced AI and IoT to drive breakthroughs in edge AI applications, particularly within the automotive, AIoT and Consumer Electronics sector. Harnessing generative AI and deep learning, our team has excelled in developing high-performance AI Inference Accelerators that redefine industry benchmarks. With a robust background pursued via MSc. in Information and communication engineering with majors in AI at TU Darmstadt (Germany) , I contribute to product-market fit analyses and optimization of Deep learning models for Videantis' cutting-edge processor IP. My pursuit of Business Management and Analytics Program at India's Premier Institute for Business management, IIM Ahmedabad enriches my strategy-development skills, ensuring our technological solutions are not only innovative but also commercially viable.
● System Architecture: Designing and building a proprietary enterprise AI operating system (OS) driven by autonomous agentic workflows. ● Cross-Vertical Scale: Architecting scalable multi-agent frameworks capable of orchestrating complex reasoning tasks across diverse industry verticals. ● Deep Tech Integration: Developing specialized AI infrastructure tailored for high-tech manufacturing, hardware engineering, and complex supply chain domains. ● Performance Engineering: Optimizing high-throughput agent loops, memory management systems, and state-machine architectures for minimal latency and maximum reliability.
Led Development of Deep Learning, Computer Vision, Edge AI software architecture. Worked closely with CTO and product leadership and cross-functional team across Europe to architect next generation AI systems for Automotive, AIoT and On-Device and On-prem platforms. Led the benchmarking of Transformers, LLM-derived models to study their feasibility for Inference on the Edge Accelerators. Also studied the feasibility for agentic behaviours.
* Deep learning and Computer vision Application Framework Development for Edge Acceleration. * Comparative Analysis and Optimization of Various Deep Neural Network such Transformers and LLMs driven by Multiple Objectives. * BenchMarking of Various Deep Neural Architectures with Industry-Standard Datasets for Videantis Deep Learning Enabled Processor IP. *Design space Exploration of Various Neural Networks for Automotive Market and Non- Automotive Market use cases for Videantis Deep Learning Enabled Processor IP. * Product-Market Fit Analysis and Suitability study for new Emerging Deep Learning algorithms.
Spearheaded Deep Learning, Computer Vision and early Agentic AI systems. Built model import stack, ONNX-C++ AI toolchains, LLM/transformer Benchmarking for Edge Deployments and handled Software Life Cycle. Contributed to EU R&D projects, mentored colleagues and worked closely with CTO and OEMs to shape next-gen autonomous intelligence.
Masters in Information and Communication Engineering with major Focus subject/research areas such as Computer Vision, Image Processing, Neural Networks, Machine Learning: Statistical Approaches., Probabilistic Graphical Models, Deep learning (Deep Neural Networks). Other Subjects: Advance Image processing, Digital Signal Processing, Hardware Description Language, Microprocessor and Embedded Systems and Wireless Communication (Game theory in Wireless Networks)
Student Research Assistant at Visual Inference Group, TU Darmstadt. Deep learning Project using Lasagne and Theano backend in Python for Neural Style Transfer. Deep learning research Project lab In computer vision: Extending Flownet with Deep domain adaptation and multi- resolution using Deep learning for optical flow estimation.
Course Mentoring for new International Students in Elecrical Engineering Fachbereich at TU Darmstadt.
Master Thesis on Deep Learning on Embedded Platforms for Computer vision, Grade: 1.3
Software development in .Net and Infrastructure Management of .Net Web Application Servers using ITIL methods for U S based Insurance client.