Ahmad Yar
Robotics and Ai Engineer Remote (Contract) @Mcattoh
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WORK HISTORY
Robotics and Ai Engineer Remote (Contract) @Mcattoh
London, GB
Working on robotics-focused AI systems with emphasis on perception, autonomy, and intelligent decision-making.Responsibilities include: •Developing and integrating ROS2-based robotics pipelines for perception and navigation • Implementing computer vision and visual perception modules for real-world robotic systems • Designing LLM-powered components for task planning, knowledge retrieval, and system intelligence • Building Retrieval-Augmented Generation (RAG) and Agentic RAG pipelines for robotics and decision support use cases • Prototyping and evaluating AI-driven solutions for autonomous systems and real-world deploymentThis is a remote, contract-based role focused on applied engineering, prototyping, and real-world system development.Responsibilities include designing and implementing robotics and AI components for intelligent systems, with emphasis on perception, autonomy, and software integration. Work involves building functional prototypes, integrating ROS2-based pipelines, and developing AI-driven modules for decision-making and perception.Contributed upstream C++ fixes to Google WebRTC, improving gRPC signaling thread safety and runtime stability; changes merged after code reviewThe role is hands-on and delivery-oriented, contributing directly to product-level features rather than academic research.
EDUCATION
University of Surrey
Master's degree, Computer vision robotics and Machine learning
Peshawar Public school
Matraculation, Science
University of Engineering & Technology Peshawar
Bachelor of Science - BS, Computer Software Engineering
University of Surrey
Computer vision robotics and ML, Robotics Technology/Technician
ABOUT AHMAD YAR
Robotics & AI Engineer with 10+ years of software engineering experience, combining a strong background in production mobile systems with hands-on work in robotics, autonomous navigation, and applied AI. I focus on building deployable, real-world systems where software meets the physical world.I specialise in robotics and autonomous systems, developing ROS 2–based pipelines for perception, navigation, and sensor fusion using LiDAR, cameras, IMU, and wheel odometry. My work includes SLAM, Nav2, Gazebo-based simulation, and deployment on embedded platforms such as Jetson Nano, with strong emphasis on real-world testing and system integration.From an AI perspective, I focus on applied machine learning and computer vision rather than academic prototypes. This includes YOLOv8-based perception, multimodal AI pipelines, and data-driven prediction systems combining structured data, text, and visual inputs. I also build LLM-powered systems using RAG and Agentic RAG for intelligent automation and decision support.I actively contribute to and work with open-source systems, including upstream C++ contributions to Google WebRTC, improving gRPC signaling thread safety and runtime stability (merged after review). I also leverage the Hugging Face ecosystem to adapt transformer-based models for production-oriented pipelines, prioritising deployability, performance, and cost efficiency.A key differentiator in my profile is the ability to bridge robotics, AI, and mobile systems. Alongside robotics and AI, I bring extensive experience in production iOS engineering, having shipped multiple applications end-to-end using Swift and Objective-C, enabling seamless user-facing control and monitoring of intelligent systems.Core focus areas:Robotics & Autonomous Systems (ROS 2, SLAM, Sensor Fusion) • Computer Vision & Perception (YOLOv8, OpenCV) • Applied ML • LLM Systems (RAG, Agentic RAG) • Open-Source AI • Mobile & Edge-AI IntegrationI’m currently exploring opportunities in AI-driven robotics and intelligent systems, especially teams building deployable autonomy, perception, and product-level technology.
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