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Principal Software Lead, Machine Learning

Roles & Responsibilities

  • 5+ years of AI modeling experience in 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; experience with diffusion and autoregressive models in a professional setting
  • Familiarity with training, inference, and infrastructure pipelines from camera input to trajectory output for self-driving or robotics; reinforcement learning experience
  • Strong understanding of modern ML architectures and training techniques; experience with model debugging, optimization, performance tuning, and implementing ML research papers

Requirements:

  • Design and implement state-of-the-art ML models and training pipelines for robotics applications; develop data strategies; implement evaluation frameworks and metrics
  • Lead rapid experimentation and prototyping of new model architectures; optimize performance and debugging; apply transfer learning and fine-tuning
  • Build robust evaluation, debugging, and interpretability tools; analyze model behavior and failure modes; track and improve model metrics
  • Collaborate with the engineering team to optimize training infrastructure and deployment from training to inference

Job description

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 Principal Machine Learning Lead 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 5+ 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.

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