Senior AI/ML Expert

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