Helix AI Engineer, Pretraining
Figureai•5h ago
United StatesOnsite$200K–$400KFull-timeMid Level3+ yrs exp
Top focus
Ai Engineer
- Figure is an AI robotics company developing autonomous general-purpose humanoid robots. Our goal is to build embodied AI systems that can perceive, reason
- act in the real world. Figure is headquartered in San Jose, CA
- this role requires 5 days/week in-office collaboration.
- Our Helix team is responsible for developing the core AI systems that power humanoid autonomy. We are looking for a Helix AI Engineer, Pretraining to build large-scale foundation models that learn from diverse data sources including text, images, video
- robot-collected experience.
- This role focuses on advancing pretraining methods that enable generalization, reasoning, and adaptability—forming the backbone for downstream capabilities in perception, planning, and action.
- Responsibilities
- Design and train large-scale foundation models across multimodal data (e.g., text, vision, and robot data)
- Develop pretraining strategies that improve generalization, reasoning, and transfer to downstream embodied tasks
- Explore and implement architectures including transformer-based and emerging foundation model paradigms
- Work on scaling laws, dataset mixture design, and training dynamics for frontier models
- Build and optimize large-scale distributed training pipelines across multi-node GPU clusters
- Collaborate closely with video, generative, agent, and robot learning teams to integrate pretrained models into the autonomy stack
- Design evaluation frameworks to measure reasoning ability, robustness, and cross-domain generalization
- Contribute to post-training approaches including fine-tuning, alignment, and model adaptation
- Requirements
- Experience training large-scale foundation models or working on pretraining for LLMs or multimodal systems
- Strong understanding of modern deep learning architectures, especially transformers
- Experience with large-scale distributed training and optimization
- Proficiency in Python and deep learning frameworks such as PyTorch
- Strong experimental rigor and ability to iterate on model design and training strategies
- Solid software engineering skills and ability to build scalable, reliable systems
- Ability to operate independently and drive ambiguous, high-impact technical problems
- Bonus Qualifications
- Experience working on frontier foundation models at companies such as Anthropic, OpenAI, Google DeepMind, or xAI
- Experience with multimodal pretraining (vision-language or vision-language-action models)
- Background in scaling laws, dataset curation, and large-scale data mixture optimization
- Experience with post-training techniques such as RLHF, reward modeling, or alignment methods
- Familiarity with embodied AI, robotics, or real-world deployment constraints
- Publication record in machine learning, NLP, or multimodal AI
- The US base salary range for this full-time position is between $200,000 - $400,000
- The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills
- 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.
Required skills
PythonPyTorchdeep learningtransformersdistributed trainingmodel designdata optimization