Posted 2 months ago
Member of Technical Staff - World Models
@ Veeda AI
Toronto, Ontario
Overview
Veeda AI is hiring a Member of Technical Staff to build multimodal foundation world models for Physical AI. The role designs, trains and scales generative and predictive models across visual and spatial data, with a strong focus on evaluation and experimentation. The posting requires a PhD or equivalent experience and hands-on distributed training with PyTorch.
Responsibilities:
- Design, train and scale generative and predictive models
- Develop multimodal learning and control methods
- Improve sequence modeling consistency and robustness
- Explore post-training and efficiency techniques
- Build evaluations and run controlled experiments
Requirements summary:
- PhD in Computer Science, Engineering or related field, or equivalent experience
- End-to-end training of foundation models
- Strong PyTorch and distributed training skills
- Independent design and analysis of ML experiments
- Experience developing model evaluations
Tools & skills
Source and dates
Employer career site / ATS feed · ashby
- Employer posting date
- 2026-09-07
- First seen by our source
- 2026-10-08
- Source record updated
- 2026-10-22
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Mid level |
| Department | Software development |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Doctorate (required) |
| Fields of study | Computer Science, Engineering |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Veeda AI
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
Scaling Physical AI through Interactive Learning in Simulated Reality
Full company description
Scaling Physical AI through Interactive Learning
- People associated on LinkedIn
- 3
- Other recorded names
- Veeda AI
- Profile identifies a recruitment agency
- No
Scaling Physical AI through Interactive Learning
| Field | Value |
|---|---|
| Industry | Artificial Intelligence |
| Company size | 11-50 employees |
| Organization type | Privately Held |
| Year founded | 2026 |
| Open jobs on Jobsy | 10 |
| View page |
Member of Technical Staff – World Models
About Us
Veeda AI is building the next generation of multimodal foundation world models for Physical AI. We're a small, fast-moving team of engineers and researchers from leading AI labs, tackling some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence. If you're excited about pushing the boundaries of what's possible with Physical AI, you'll have the opportunity to make an outsized impact from day one.
Responsibilities
Model Research & Development: Design, train, and scale generative and predictive models across visual and spatial modalities.
Multimodal Learning & Control: Develop methods for learning from diverse data sources and incorporating conditioning signals into model behavior.
Sequence Modeling: Improve consistency, robustness, and generalization in models of complex temporal and spatial structure.
Post-Training & Efficiency: Explore post-training and model optimization techniques to improve quality, controllability, and computational efficiency.
Evaluation & Experimentation: Develop rigorous evaluations, conduct controlled experiments, and use findings to guide modeling and data decisions.
Research Collaboration: Work closely with data, systems, and robotics engineers to translate research ideas into reliable capabilities.
Requirements
PhD degree in Computer Science, Engineering, or a related technical field, or equivalent experience.
Experience training machine learning foundation models end to end, with strong PyTorch skills and hands-on experience in distributed training.
Ability to independently design, execute, and analyze machine learning experiments, from hypothesis through ablation to conclusion.
Experience developing evaluations that reveal model limitations and inform research decisions.
Nice to Have
Strong publication record or substantial contributions to research on image, video, 3D, or multimodal models.
Experience with learned representations, compression, or tokenization for high-dimensional data.
Experience with conditional generation, temporal consistency, or long-context modeling.
Experience with reinforcement learning, model-based learning, or embodied AI.
Experience with post-training, distillation, or efficient inference for generative models.
Experience working with large-scale, heterogeneous visual or sensor datasets.
Contributions to open-source machine learning projects or research infrastructure.
Journal
Only you can see this. Kept on this device, and in your account when you sign in.