AI Engineer, Post-Training - Helix Team
Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot, Figure 02, is designed for commercial tasks and the home. We are based in San Jose, CA and require 5 days/week in-office collaboration. It’s time to build. Figure’s vision is to deploy autonomous humanoids at a global scale. Our Helix team is looking for anAI Engineer, Post-Trainingto work on enhancing and deploying state-of-the-art AI models. You will focus on improving large pre-trained models for practical applications, ensuring that they are reliable, efficient, and scalable. You will collaborate closely with research and product teams to develop new techniques for optimizing AI systems, and help integrate advanced AI capabilities into products and services. Responsibilities: Requirements: Bonus Qualifications: The US base salary range for this full-time position is between $175,000 - $350,000 annually. The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended. - Lead the post-training research to improve performance, safety, and generalization of large-scale AI models. - Work with cross-functional teams to deploy AI solutions in real-world applications, focusing on improving the user experience and model performance. - Develop and implement novel approaches to model fine-tuning, optimization, and evaluation. - Design and conduct experiments to better understand model behavior and to identify and mitigate risks related to fairness, safety, and reliability. - Collaborate with other researchers, engineers, and product teams to align model development with company goals. - Contribute to cutting-edge research and bring new insights to the team to solve complex problems in AI deployment. - Strong background in machine learning, deep learning, and natural language processing (NLP). - Proven experience in model development, tuning, and evaluation with large-scale neural networks. - Familiarity with AI safety and robustness challenges in real-world environments. - Proficiency in programming languages such as Python, with experience in machine learning frameworks like TensorFlow, PyTorch, or similar. - Experience working with large codebases and distributed computing environments. - Ability to conduct independent research and collaborate effectively in a team-oriented environment. - A Masters or PhD or equivalent experience in a relevant field (e.g., Computer Science, Machine Learning, AI, or related disciplines). - Prior experience working with robotic learning systems
Location: San Jose, CA
Salary range: None - None