AI Engineer

Role Overview

We are seeking a highly skilled AI Engineer to develop the core intelligence layer of an advanced robotic system operating in real-world environments. The ideal candidate will work on integrating perception, language, memory, reasoning, and control systems to create a unified embodied AI agent capable of understanding, planning, and acting autonomously.

Responsibilities

• Design and develop Vision-Language-Action (VLA) pipelines that connect perception, reasoning, and robotic control.
• Integrate visual embeddings, Large Language Models (LLMs), and robotic control interfaces into a cohesive system.
• Translate high-level user goals into executable robotic actions.
• Build and maintain agentic systems with memory, state management, and environmental awareness.
• Ground language understanding in real-time sensory observations.
• Develop planning and re-planning capabilities based on dynamic environmental feedback.
• Implement real-time multimodal inference loops combining vision, language, and control.
• Orchestrate interactions between perception models, language models, planners, and robotic controllers.
• Design scalable, modular, and maintainable AI system architectures.
• Collaborate with robotics, software, and research teams to deploy intelligent autonomous systems.

Requirements

• Strong experience working with Large Language Models (LLMs) and multimodal AI systems.
• Solid understanding of Transformer architectures.
• Experience with Vision-Language Models (VLMs) and CLIP-style models.
• Hands-on experience building agentic AI systems, including tool/function calling and memory management.
• Proficiency in Python programming.
• Experience developing asynchronous and real-time processing pipelines.
• Strong systems engineering mindset with a focus on modular architecture, integration, and orchestration.
• Ability to design and deploy end-to-end AI solutions in production environments.

Nice to Have

• Experience in Embodied AI, Robotics, or Autonomous Systems.
• Knowledge of Reinforcement Learning (RL) and Behavior Cloning techniques.
• Familiarity with classical or neural planning systems.
• Experience working with multimodal datasets involving vision, language, and action.
• Hands-on experience with simulation environments such as Isaac Sim, Habitat, or Gazebo.

Benefits

• Health insurance
• Paid sick time
• Paid time off

Skills

• Python
• Large Language Models (LLMs)
• Transformer architectures
• Vision-Language Models (VLMs)
• Reinforcement Learning (RL)