About Standard Bots

At Standard Bots, we're revolutionizing real-world automation by making robotic systems accessible to everyone. Our AI-powered platform enables robots to tackle unprecedented challenges through an intuitive instruction interface, bringing the power of software automation to physical spaces.

About the Role

We're seeking a Senior Machine Learning Engineer to develop and optimize our AI models and training systems. This is an exciting opportunity to apply your deep ML expertise to cutting-edge AI/robotics applications. You'll work closely with our engineering team to design, implement, and iterate on large-scale AI models while building efficient systems for rapid experimentation and deployment.

💡Experience with AI or robotics isn’t required; we’re looking for experienced engineers ready to make a tangible impact in the AI robotics revolution. If you're excited about building scalable systems and want to transition into the AI/robotics space, we’d love to hear from you.

In this role, you will:

• Design and implement state of the art ML models and training pipelines:

  • Apply novel machine learning techniques to wide range of robotics applications 

  • Develop efficient data and training strategies

  • Implement model evaluation frameworks and metrics tracking

• Lead model development and iteration with focus on:

  • Rapid experimentation and prototyping of new model architectures

  • Performance optimization and model debugging

  • Transfer learning and fine-tuning strategies

• Build robust evaluation and debugging systems to:

  • Analyze model behavior and failure modes

  • Implement interpretability tools and visualization frameworks

  • Track and improve model metrics

• Collaborate with engineering team to optimize training infrastructure and deployment

You might thrive in this role if you:

• Have 5+ years of software engineering experience, with ML experience

• Proven track record developing and deploying large-scale ML models

• Strong understanding of modern ML architectures and training techniques

• Experience with model debugging, optimization, and performance tuning

• Background in implementing ML research papers and adapting academic work

Tech Stack

• PyTorch

• Python

• NodeJS/Typescript

• Docker