Research Scientist
| Company | Scaled Foundations |
|---|---|
| Location | Redmond, WA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- PhD in Computer Science, Robotics, relevant technical field, or equivalent practical experience.
- Research experience in machine learning, robotics, and computer vision.
- Programming experience in Python/C++.
- Detailed understanding of deep learning frameworks like Pytorch or Jax.
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
- First author publications at major AI and robotics conferences (e.g., NeurIPS, CVPR, ICCV, ICML, ICLR, ICRA, IROS).
Responsibilities
- Independently implement state of the art multimodal machine learning models and techniques for robotics.
- Independently identify and execute on reasonable medium to large scale research ideas with many tasks. Apply robotics model improvements to relevant business needs.
- Come up with well thought out hypotheses with a clear focus. Independently design, run, and evaluate experiments to validate these hypotheses.
- Independently identify and debug common issues in training machine learning models such as overfitting/underfitting, efficiency bottlenecks etc.
- Work with high fidelity simulation platforms for synthetic data generation at a large scale.
- Keep up to date with the state of the art in multimodal machine learning and foundation models for robotics applications.
- Lead publications and open-sourcing efforts. Communicate your learnings effectively to various stakeholders.
Preferred Qualifications
- Experience with developing robotics algorithms or machine learning models at scale.
- Detailed understanding of large language models (LLMs) and the Transformer model architecture. Experience with training Transformers for multimodal data.
- Experience with high fidelity simulation platforms such as AirSim, CARLA, Isaac Sim among others.
- Good understanding of systems considerations and the ability to factor these into model choices. Experience building efficient robotics pipelines involving sensor fusion and model inference.
- Experience with optimizing and running machine learning models on real robots or edge hardware like Nvidia Jetson, while balancing model performance with latency / compute etc.
- Proven track record of achieving significant research results and innovation.