Staff AI Research Engineer
At a glance
Senior AI Research role at Standard Bots. New York City · full-time · $250,000–$300,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build machine-learning models and training pipelines for robotics problems, using new techniques across a range of applications
- Run quick architecture experiments, then improve model speed and debug issues as development progresses
- Create evaluation and debugging systems to examine model behavior, surface failures and track performance
- Work with engineering to improve training infrastructure and move models toward deployment
- Develop data and training approaches that support large-scale model development
What you bring
- You have seven or more years modeling AI in self-driving cars, or a PhD plus at least three years in that field
- You have used diffusion and autoregressive methods professionally and have a record of deploying large-scale ML models
- You have worked with PyTorch, which is required for this role
- You can work with camera-to-trajectory pipelines for self-driving or robotics, and have experience with reinforcement learning
Who this fits
This staff-level role suits an experienced ML engineer who can work across the stack on model development and deployment in a small AI team. The stated experience threshold can also be met with a PhD and fewer years of self-driving-car AI modeling.
From the employer
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 Staff AI Research 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. We have a small team of AI engineers, so we’re looking for someone who is excited to work at a startup, and work across the stack to do what is needed to get a model that achieves a customer problem.
We're looking for an experienced engineer ready to make a tangible impact in the AI robotics revolution. This role requires a proven background working on ML planning within the autonomous vehicle space with experience using the latest techniques in diffusion and autoregressive models in a professional setting. If you're excited about building the latest advancements in AI and working in the 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 7+ years of AI modeling experience, specifically within the self-driving car industry (or PhD with 3+ years of AI modeling experience in the self-driving car industry)
Proven track record developing and deploying large-scale ML models
Have experience using the latest techniques in diffusion and autoregressive models in a professional setting
Are familiar with training inference and infra pipelines that go from camera input to trajectory output for self driving or robotics
Have experience with RL (reinforcement learning)
Have a strong understanding of modern ML architectures and training techniques
Have experience with model debugging, optimization, and performance tuning
Have a background in implementing ML research papers and adapting academic work
Tech Stack
PyTorch (experience with PyTorch required)
Python
NodeJS/Typescript
Docker
Compensation and Benefits:
The salary range for this role is $250,000 to $300,000, depending on experience. We are open to a variety of seniority levels for this role and will build compensation packages that are commensurate with seniority and skill level. Base salary is just one part of the overall compensation at Standard Bots. All Full-Time Employees are eligible for Employee Stock Options. We also offer a package of benefits including paid time off, medical/dental/vision insurance, life insurance, disability insurance, and 401(k) to regular full-time employees.