Application Guide

How to Apply for Senior ML Engineer (Energy & Utilities)

at AZX, PBC.

🏢 About AZX, PBC.

AZX, PBC. is a public benefit corporation founded in 2024, specializing in AI transformation for critical industries like energy and utilities. They are profitable from inception and work with industry leaders, focusing on climate and sustainability challenges through physics-informed ML and enterprise AI solutions. This is a chance to join a fast-growing, mission-driven company where your work directly accelerates positive impact.

About This Role

As a Senior ML Engineer, you'll build reusable AI models and infrastructure for utility clients, including a fast building-energy simulation engine and tools for real-time grid sensor data. Your work will be open-sourced, impacting external engineers and contributing to decarbonization efforts. This role is central to AZX's mission of applying AI to solve climate challenges, making it highly impactful.

💡 A Day in the Life

A typical day might involve collaborating with a team to design a new ML model for demand forecasting, then implementing the underlying data pipelines to ingest real-time grid data. You could also spend time optimizing the building energy simulation engine for speed, and later participate in a code review for an open-source utility library. Your work directly contributes to client projects and the broader AI for climate community.

🚀 Application Tools

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Interview Prep

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🎯 Who AZX, PBC. Is Looking For

  • Experienced in ML engineering with a strong background in physics-informed models or scientific machine learning.
  • Proficient in building scalable infrastructure, including data pipelines, APIs, and simulation engines.
  • Familiar with energy systems, building energy modeling, or utility data (e.g., smart meter data, grid sensors).
  • Comfortable with open-source development and collaborating with external contributors.
  • Passionate about climate tech and sustainability, with a desire to work in a fast-paced startup environment.

📝 Tips for Applying to AZX, PBC.

1

Highlight any experience with building energy simulation tools (e.g., EnergyPlus, OpenStudio) or physics-informed neural networks (PINNs) in your resume and cover letter.

2

Showcase open-source contributions or projects, as AZX values work that is shared with the community.

3

Tailor your application to mention specific client industries (e.g., utilities, real estate) and how your skills can solve their unique challenges.

4

Quantify the impact of your past work, especially if it involved energy savings, efficiency improvements, or large-scale data processing.

5

Since AZX is a public benefit corporation, emphasize your alignment with their mission and your commitment to positive societal impact.

✉️ What to Emphasize in Your Cover Letter

["Explain why you're drawn to AZX's mission of accelerating positive impact in critical industries, and how your skills align with their focus on climate and sustainability.", 'Detail your experience with physics-informed ML and how it applies to energy or utilities, providing specific examples of projects.', 'Emphasize your ability to build reusable tools and infrastructure that can be leveraged across multiple engagements, as this is key to the role.', 'Mention your comfort with open-source development and your enthusiasm for contributing to publicly available resources.']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Research AZX's open-source projects and contributions on GitHub to understand their tech stack and engineering practices.
  • → Look into their client case studies (e.g., CBRE, LevelTen Energy) to see how they apply AI in real-world scenarios.
  • → Familiarize yourself with the public benefit corporation model and what it means for AZX's operations and culture.
  • → Stay updated on the latest trends in physics-informed ML and building energy modeling to demonstrate your expertise.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 How would you approach building a fast building-energy simulation engine? Discuss trade-offs between accuracy and speed.
2 Describe a time you worked with real-time sensor data. What challenges did you face and how did you handle them?
3 Explain how you would incorporate physics-based constraints into a machine learning model for energy forecasting.
4 How do you ensure your code is reusable and maintainable for a variety of clients? Provide examples.
5 What experience do you have with open-source projects, and how would you encourage external contributions?
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⚠️ Common Mistakes to Avoid

  • Submitting a generic application that doesn't mention climate, energy, or sustainability.
  • Overlooking the importance of infrastructure and tooling, focusing only on model development.
  • Failing to show specific examples of how you've built reusable systems or contributed to open-source.
  • Not demonstrating an understanding of the utility industry's unique data challenges and regulatory constraints.

📅 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 AZX, PBC.!

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