AI Engineer, Post-training - Helix Team

Figure AI Figure AI · Robotics · AI - Helix Team

AI Engineer focused on post-training of large AI models for humanoid robotics, involving fine-tuning, optimization, evaluation, and safety, with a secondary focus on integrating these models into agentic systems for real-world applications.

What you'd actually do

  1. Lead the post-training research to improve performance, safety, and generalization of large-scale AI models.
  2. Work with cross-functional teams to deploy AI solutions in real-world applications, focusing on improving the user experience and model performance.
  3. Develop and implement novel approaches to model fine-tuning, optimization, and evaluation.
  4. Design and conduct experiments to better understand model behavior and to identify and mitigate risks related to fairness, safety, and reliability.
  5. Collaborate with other researchers, engineers, and product teams to align model development with company goals.

Skills

Required

  • machine learning
  • deep learning
  • natural language processing (NLP)
  • model development
  • model tuning
  • model evaluation
  • large-scale neural networks
  • AI safety
  • robustness
  • Python
  • TensorFlow
  • PyTorch
  • large codebases
  • distributed computing environments
  • independent research
  • team collaboration
  • Masters or PhD or equivalent experience

Nice to have

  • robotic learning systems

What the JD emphasized

  • post-training research
  • fine-tuning
  • optimization
  • evaluation
  • AI safety
  • robustness

Other signals

  • post-training research
  • deploying state-of-the-art AI models
  • improving large pre-trained models for practical applications
  • fine-tuning, optimization, and evaluation
  • AI safety and robustness challenges