Application Guide

How to Apply for AI & ML Engineer

at Built Robotics

🏢 About Built Robotics

Built Robotics is at the forefront of automating heavy equipment for the construction and solar industries, with a mission to accelerate the transition to clean energy. Their focus on edge AI and autonomy in rugged environments makes them a unique blend of robotics, machine learning, and renewable energy.

About This Role

As an AI & ML Engineer, you will design and deploy edge machine learning systems that enable construction robots to operate autonomously and safely. Your work will directly impact the efficiency of solar farm installations, contributing to faster renewable energy deployment.

💡 A Day in the Life

A typical day might start with a stand-up to discuss progress on model training pipelines, followed by debugging a sensor fusion issue on a test robot. After lunch, you might optimize a computer vision model for inference on an edge device, then review deployment metrics and plan next experiments.

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🎯 Who Built Robotics Is Looking For

  • Strong background in computer vision and sensor fusion, with experience applying these to real-world robotics or autonomous systems.
  • Proven track record of deploying ML models to edge devices (e.g., NVIDIA Jetson, embedded systems) with latency and power constraints.
  • Expertise in building scalable ML infrastructure, including data pipelines, distributed training, and model monitoring in production.
  • Passionate about clean energy and eager to solve challenging problems in unstructured outdoor environments.

📝 Tips for Applying to Built Robotics

1

Highlight any experience with construction or outdoor robotics, even if from side projects or research, to show domain understanding.

2

Emphasize projects where you optimized models for edge deployment (e.g., quantization, pruning, TensorRT) and include performance metrics.

3

Tailor your resume to mention specific ML frameworks (PyTorch, TensorFlow) and tools (Kubeflow, MLflow, Docker) that align with scalable infrastructure.

4

Include a link to your GitHub or portfolio with relevant code, especially if you have open-source contributions to robotics or ML.

5

In your cover letter, connect your work to Built Robotics' mission of accelerating solar energy, showing genuine interest in the industry.

✉️ What to Emphasize in Your Cover Letter

['Your experience with edge ML and computer vision in real-world applications.', 'How you have built scalable ML pipelines that handle large datasets and continuous model updates.', 'Your passion for renewable energy and autonomous systems, and why Built Robotics specifically excites you.', 'A specific example of solving a challenging problem related to sensor fusion or model optimization for safety-critical systems.']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Read Built Robotics' blog posts or press releases about their autonomous solar installation robots.
  • → Understand their technology stack: they use NVIDIA Jetson for edge computing and ROS for robotics.
  • → Look into their safety certifications and how they handle edge cases in construction environments.
  • → Check recent job postings for similar roles to see if they mention specific projects like 'RPD 35' or 'autonomous excavators'.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Design a computer vision pipeline for detecting construction obstacles in real-time on an edge device.
2 How would you approach sensor fusion (e.g., cameras, LiDAR, GPS) for robot localization in dusty environments?
3 Explain how you would set up a distributed training system for a large model using PyTorch and Kubernetes.
4 Discuss a time you debugged a model performance issue in production; what metrics did you monitor?
5 How would you validate the safety of an ML model before deploying it to a construction site?
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⚠️ Common Mistakes to Avoid

  • Submitting a generic resume that doesn't highlight edge deployment or ML infrastructure experience.
  • Ignoring the company's mission; failing to express genuine interest in clean energy or construction automation.
  • Overlooking the importance of safety; not discussing how you ensure model reliability and fail-safes.

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Built Robotics!

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