Title: Senior AI/ML Expert Working Mode: Remote Experience: 2-4 Years About the Company: MNR Technologies is an AI-first product company building real-world, production-grade intelligent systems across industries. We work on cutting-edge areas including LLMs, agentic AI, RAG systems, computer vision, edge AI, and autonomous systems, focusing on scalable solutions that deliver measurable business impact. Role Overview: We are looking for an AI/ML engineer who can build production-grade AI systems that operate in real-world environments. This role goes beyond experimentation—you will design, develop, and deploy robust AI systems across LLMs, computer vision, and autonomous systems, including simulation-driven development and robotics workflows. You should be comfortable owning problems end-to-end—from idea → architecture → deployment → scaling → business impact. Key Responsibilities: Design and build production-ready AI/ML systems with high reliability and scalability Work extensively with LLMs, RAG pipelines, and agentic frameworks Fine-tune and optimize models for real-world performance and efficiency Develop and deploy edge AI and computer vision solutions Architect and implement distributed, high-availability AI systems Optimize workloads across GPU architectures and compute environments Build on-demand LLM systems and intelligent automation pipelines Autonomous Systems & Robotics (Core Focus) Develop and research robotics teleoperation systems in simulation (MuJoCo, Isaac) Build scene and task generation toolchains in robotics simulators Develop reactive 3DGS-based end-to-end autonomous driving (E2E-AD) closed-loop simulators Deploy and train E2E-AD algorithms (UniAD, VAD, VADv2, etc.)

Requirements

Required Skills and Experience: 2–4 years of hands-on experience in AI/ML product development Strong experience with LLMs, RAG systems, and agentic AI workflows Solid background in computer vision and deep learning Experience with simulation environments (MuJoCo, Isaac, or similar) Understanding of GPU architecture and performance optimization Experience building scalable, distributed systems Strong foundation in algorithms, optimization, and system design Proficiency in Python and modern ML/DL frameworks Experience in end-to-end product development (not just research) Understanding of product-market fit and go-to-market strategies Ability to translate business problems into scalable AI solutions Exposure to business architecture and product commercialization is a plus Entrepreneurial mindset or prior experience building products Nice to Have: Experience with robotics, autonomous driving, or real-time AI systems Knowledge of MCP (Model Context Protocol) and advanced agent frameworks Exposure to AI-powered quantum technologies Advanced prompt engineering capabilities