5 days ago
Base Salary
$273k - $321k/yr
Responsibilities
- Define and build technical architecture for world models and foundation models for physical AI.
- Develop large-scale multimodal models that learn representations of complex, dynamic physical environments.
- Research self-supervised, generative, predictive, and representation-learning approaches for physical-world intelligence.
- Develop methods for modeling how environments evolve and how actions affect future states.
- Make architectural decisions spanning data, model design, pretraining, fine-tuning, evaluation, inference, and deployment.
- Establish evaluation methodologies for physical-world understanding, representation, and prediction.
- Translate emerging research into machine learning systems capable of operating on real machines.
- Provide technical leadership through research direction, architecture reviews, mentorship, experimentation, and hands-on engineering.
- Partner with perception, action-model, robotics, autonomy, simulation, and ML infrastructure teams.
- Help establish the technical bar for the AI Research organization and assess engineering and research talent.
Requirements
- Deep expertise in machine learning and experience developing large-scale deep learning or foundation-model systems.
- Strong understanding of modern model architectures and representation learning.
- Experience with multimodal learning, video models, generative models, self-supervised learning, predictive models, spatial intelligence, or embodied AI.
- Experience training models on large-scale datasets and understanding the relationship between data, architecture, compute, and model performance.
- Strong understanding of the full machine learning lifecycle, including data strategy, architecture, training, evaluation, optimization, and inference.
- Experience translating research ideas into functioning machine learning systems.
- Strong software engineering fundamentals and hands-on proficiency in Python and modern machine learning frameworks.
- Ability to operate in ambiguous research environments and make consequential technical decisions that influence research or engineering direction.
- Ability to communicate complex research and technical ideas clearly and collaborate across research, engineering, and robotics disciplines.
Benefits
- Medical, dental, vision, disability, and life insurance.
- Flexible Spending Account and Health Savings Account options.
- 401(k), equity eligibility, sick time, unlimited flexible time off, and paid holidays.
- Paid parental leave and a pre-tax commuter benefit plan.
- Team lunch in the SoMa office every Tuesday and Thursday.
- Based in the San Francisco office with onsite work five days per week.
Tech Stack
Categories
AI ResearchML Engineering
About Atoms
Atoms develops robotics, software, and infrastructure to automate real-world industrial operations, with offerings focused on food production, mining, and robotic transport platforms. It sells integrated automation systems and platforms—Atoms Food, Atoms Mining, and a transport wheelbase for robots—to industrial customers seeking greater productivity and scalability. The privately held company is headquartered in Los Angeles.