Senior AI Research Engineer — Robotics & Diffusion ML

Standard Bots; United States; Remote; USD 250,000 - 300,000; Full time

Benefits offered by this job

Employee Stock Options

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

401(k)

Job summary

Standard Bots is seeking a Staff AI Research Engineer to design and optimize large-scale AI models and training systems for robotics applications. You will blend deep ML expertise with scalable infrastructure in a startup environment.

Work across the stack with an agile team to deliver practical models from research to deployment, focusing on diffusion and autoregressive techniques, RL, and real-world robotics challenges.

Qualifications

• 7+ years of AI modeling experience in self-driving or related robotics.
• Proven track record deploying large-scale ML models.
• Experience with diffusion and autoregressive models in a professional setting.
• Experience with training/inference and infra pipelines from camera input to trajectory output for robotics.
• Experience with RL (reinforcement learning).
• Strong understanding of modern ML architectures and training techniques.

Responsibilities

• Design and implement state of the art ML models and training pipelines.
• Lead model development and iteration with focus on improving performance and reliability.
• Build robust evaluation and debugging systems for rapid experimentation.
• Collaborate with engineering to optimize training infrastructure and deployment.

Skills

AI modeling experience

Self-driving domain

Diffusion models

Autoregressive models

Model debugging & optimization

Reinforcement Learning

ML architecture & training

Experimentation pipelines

Education

PhD in AI/ML (optional with 3+ years in self-driving)

Tools

PyTorch

Python

NodeJS/TypeScript

Docker

Job description

Standard Bots is seeking a Staff AI Research Engineer to design and optimize large-scale AI models and training systems for robotics applications. You will blend deep ML expertise with scalable infrastructure in a startup environment.

Work across the stack with an agile team to deliver practical models from research to deployment, focusing on diffusion and autoregressive techniques, RL, and real-world robotics challenges.