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Devendra VyasDV

Devendra Vyas

AI/ML/MLOps | Engineer/Researcher | Py

€800/day
München, DE
3-7 years

Average response time: 1 hour

About Devendra

Experience Machine Learning Engineer with expertise in Deep Learning, Computer Vision, and Software Engineering. I specialize in designing innovative solutions for edge AI, robotics, and autonomous systems, optimizing models for real-world applications. With experience as a technical lead and a track record of publications, I bridge the gap between cutting-edge research and industry demands. I bring proficiency in deploying AI solutions, enhancing MLOps pipelines, and integrating multi-modal inputs for diverse applications. Let’s collaborate to build scalable, robust, and future-ready AI systems.

*Deutsch*

Ich bin ein erfahrener Machine-Learning-Ingenieur mit Expertise in Deep Learning, Computer Vision und Softwareentwicklung. Mein Schwerpunkt liegt auf der Entwicklung innovativer Lösungen für Edge-KI, Robotik und autonome Systeme sowie der Optimierung von Modellen für reale Anwendungen. Als technischer Leiter und mit einer Reihe von Publikationen überbrücke ich die Lücke zwischen Forschung und Industrieanforderungen. Ich bringe umfassende Erfahrung in der Implementierung von KI-Lösungen, der Verbesserung von MLOps-Pipelines und der Integration multimodaler Eingaben für vielfältige Anwendungen mit. Lassen Sie uns zusammen skalierbare, robuste und zukunftssichere KI-Systeme entwickeln.

Core skills: Python, PyTorch, TensorFlow, Knowledge Distillation, Object Detection, Semantic Segmentation, MLOps (Docker, MLFlow, AWS, GCP).
  • English

    Native or bilingual

  • German

    Conversational

Remote only
Primarily works remotely

Experience

  • Verses Technologies
    Sr. Machine Learning Engineer
    March 2025 - Today (1 year and 3 months)
    • Collaborating with external partners that work with Visual Language Action Models for Hand Grasping Robot and AR
    • Working on a multi-stage pipeline involving ISAAC Omniverse, ROS2-Nav2 Stack and a perception pipeline involving YOLO-v10
    • Exploring Use cases via developing proof-of-concept for 3D Reconstruction using Gaussian Splatting
    Computer Vision artificial intelligence
  • Dev AI Ventures
    AI Strategy Consultlant
    DIGITAL AND IT
    January 2024 - Today (2 years and 5 months)
    München, Germany
    • Advised TenderFix on transforming OCR-based workflows into RAG pipelines for enhanced document processing efficiency.
    • Scoped architecture and developed a comprehensive rollout plan to streamline implementation.
    • Delivered a VLM landscape review for Drizz.dev, providing actionable model and infrastructure recommendations.
    • Designed a deep learning-based image culling strategy for Eventgraphia, outlining a high-level system and data plan.
    Deep Learning artificial intelligence LLM Product Strategy
  • Verses Technologies
    ML Research Engineer
    December 2023 - February 2025 (1 year and 2 months)
    • Working as Technical Lead for smart-warehouse use case under the Distributed AI on Edge (dAIEdge) initiative
    • Optimizing perception to action models using Knowledge Distillation and Active Inference
    • Investigating ways to incorporate various modalities(Audio, Text and Images) into the current product that involves robot manipulation using Active Inference
    • Publication: Towards smart and adaptive agents for active sensing on edge devices, D. Vyas, M. De Prado and T. Verbelen, ExcelAIEdge 2025

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Education

  • Master of Science
    Technical University of Munich
    2023
    M.Sc. Informatics
  • Bachelor of Technology in Computer Science
    The LNM Institue of Information Technology
    2016
    B.Tech Computer Science

Skill set

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