About the job
About Standard Bots
At Standard Bots, we are pioneering the future of automation by making robotic systems accessible to all. Our innovative AI-driven platform empowers robots to address unprecedented challenges through an easy-to-use instruction interface, effectively integrating software automation into physical environments.
About the Role
We are on the lookout for a skilled AI Research Engineer to enhance and refine our AI models and training frameworks. This is a unique chance to leverage your extensive machine learning expertise in cutting-edge AI and robotics applications. You will collaborate closely with our engineering team to design, implement, and iterate on large-scale AI models, while also establishing efficient systems for swift experimentation and deployment. As part of a small team of AI engineers, we seek a candidate who is passionate about the startup environment and willing to work across the stack to develop solutions that address customer challenges.
If you have a solid background in machine learning planning within the autonomous vehicle domain and practical experience with the latest diffusion and autoregressive model techniques, we invite you to join us in making a significant impact in the AI robotics revolution. Your excitement for building advancements in AI and robotics is exactly what we are looking for.
Responsibilities:
Design and implement cutting-edge machine learning models and training pipelines:
Utilize innovative machine learning methodologies across a variety of robotics applications
Create efficient data and training strategies
Establish model evaluation frameworks and metrics tracking
Spearhead model development and iteration focused on:
Rapid experimentation and prototyping of new model architectures
Performance optimization and debugging of models
Transfer learning and fine-tuning strategies
Develop robust evaluation and debugging systems to:
Analyze model behaviors and identify failure modes
Implement interpretability tools and visualization frameworks
Monitor and enhance model metrics
Work in close collaboration with the engineering team to optimize training infrastructure.

