Helix AI Engineer, Modeling (AI)

TL;DR

Helix AI Engineer, Modeling (AI): Designing and advancing core model architectures and learning approaches for perception, reasoning, and action in embodied AI systems with an accent on representation learning, multimodal fusion, and model capabilities. Focus on improving model capabilities in areas such as generalization, robustness, and long-horizon reasoning.

Location: Must work 5 days/week in-office in San Jose, CA

Company

hirify.global is an AI robotics company developing autonomous general-purpose humanoid robots.

What you will do

• Design and develop model architectures for perception, reasoning, and action across multimodal inputs.
• Build models that learn structured representations of the world, including objects, dynamics, and interactions.
• Advance multimodal learning approaches, including fusion, alignment, and cross-modal reasoning.
• Improve model capabilities in areas such as generalization, robustness, and long-horizon reasoning.
• Collaborate with pretraining, video, generative, RL, and robot learning teams to integrate modeling advances.
• Design experiments and evaluation frameworks to understand model behavior and guide iteration.

Requirements

• Experience designing and training deep learning models for vision, language, or multimodal systems.
• Strong understanding of modern model architectures (e.g., transformers).
• Experience improving model performance through architectural innovation and experimentation.
• Proficiency in Python and deep learning frameworks such as PyTorch.
• Strong experimental rigor and ability to iterate on model design and performance.
• Solid software engineering skills and ability to build reliable, maintainable systems.

Nice to have

• Experience with multimodal models (vision-language or vision-language-action systems).
• Background in representation learning, world models, or structured prediction.
• Experience working on frontier models at companies such as OpenAI, Google DeepMind, Anthropic, Meta, or xAI.
• Familiarity with embodied AI, robotics, or real-world ML systems.
• Experience with large-scale training or distributed systems.