Job Details

A venture-backed Physical AI company based in San Francisco is partnering with us to hire an AI Engineer to work on cutting-edge multi-modal AI agent systems. This team is building intelligence that can perceive, reason, and act in the physical world by combining large language models, vision models, and real-world data streams.

About the Role

This role sits at the intersection of AI research and production engineering, focusing on building robust agent architectures capable of reasoning across text, images, video, and sensor inputs.

Responsibilities

• Design and develop multi-modal AI agents capable of reasoning across text, vision, and sensor data
• Build agent architectures leveraging vision models, and tool-use frameworks
• Implement planning, memory, and decision-making pipelines for autonomous systems
• Develop scalable inference pipelines for real-time AI applications
• Work on integrating AI models with physical systems, robotics, or sensor environments
• Optimize models and systems for latency, reliability, and real-world deployment
• Collaborate with cross-functional teams to bring AI systems from research to production

Qualifications

• Strong experience building AI agents or agentic systems
• Hands-on experience with multi-modal AI models (LLMs + Vision / Video / Sensor data)
• Strong Python skills and experience with PyTorch or similar deep learning frameworks
• Experience with LLM orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or similar)
• Experience working with tool-using agents, planning frameworks, or autonomous workflows
• Familiarity with distributed systems or production ML systems

Required Skills

• Strong experience building AI agents or agentic systems
• Hands-on experience with multi-modal AI models (LLMs + Vision / Video / Sensor data)
• Strong Python skills and experience with PyTorch or similar deep learning frameworks
• Experience with LLM orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, or similar)
• Experience working with tool-using agents, planning frameworks, or autonomous workflows
• Familiarity with distributed systems or production ML systems

Pay range and compensation package

The role is offering a salary of up to $300,000 per annum and will work on a hybrid working schedule. The role will come with a significant equity portion also.