Helix AI Engineer (Agentic Systems)

TL;DR

Helix AI Engineer (Agentic Systems): Design, train, and deploy multimodal agents that operate autonomously for hours to days with an accent on building agents that reason from raw sensory inputs, implementing episodic memory systems, and developing planning mechanisms. Focus on building reliable perception → reasoning → action loops with strong stability and failure recovery and designing evaluation harnesses, benchmarks, and metrics to measure agent reasoning.

Location: Onsite in San Jose, CA

Company

hirify.global is an AI robotics company developing autonomous general-purpose humanoid robots with human-level intelligence for home and commercial markets.

What you will do

• Design, train, and deploy multimodal agents that operate autonomously for hours to days.
• Build agents that reason from raw sensory inputs (pixels, environment state, proprioception) to structured actions.
• Implement episodic memory systems for persistent state, retrieval, and long-horizon reasoning.
• Develop planning, reasoning, and tool-use mechanisms for multi-step task execution.
• Build reliable perception → reasoning → action loops with strong stability and failure recovery.
• Design evaluation harnesses, benchmarks, and metrics to measure agent reasoning, planning, and reliability.

Requirements

• Experience building autonomous agents that run continuously and complete multi-step tasks.
• Experience developing agents that reason from pixel inputs or raw environment observations.
• Experience implementing agent memory, planning, reasoning, or tool-use systems.
• Experience training or fine-tuning multimodal or foundation models.
• Strong proficiency in Python and modern deep learning frameworks (e.g., PyTorch).
• Strong experimental rigor and ability to design, analyze, and iterate on ML systems.

Nice to have

• Experience with embodied AI, robotics learning, or robot policy training.
• Experience building multimodal foundation models (vision-language or vision-language-action).
• Background in agentic AI systems or long-horizon planning architectures.
• Experience working with large-scale distributed training systems.

Culture & Benefits

• The total compensation package may include additional components and benefits, with details shared upon an employment offer.