Application Guide

How to Apply for AI Systems Engineer (Aerospace Integrations) (DC or Philly Metro/Remote)

at Element84

🏢 About Element84

Element84 is a woman-owned small business that specializes in cloud-based geospatial data processing and Earth science systems. They work on meaningful projects that help answer big questions about our health, infrastructure, and changing planet, with a strong commitment to work-life balance and a flexible work schedule since 2010. Their values—investing in each other, reliability, and work that benefits the world—make them a unique and purpose-driven place to work.

About This Role

As an AI Systems Engineer focusing on Aerospace Integrations, you'll be at the forefront of applying AI/ML to geospatial and remote sensing data, building systems that support Earth observation and aerospace missions. This role is impactful because you'll be creating pipelines and software that enable scientists and analysts to derive critical insights from satellite and aerial data, contributing to global understanding and decision-making.

💡 A Day in the Life

You'll likely start your day with a team standup to coordinate tasks, then dive into designing or refining data pipelines, coding, and testing AI models. You might collaborate with scientists or engineers to integrate new data sources, and you'll have time for deep work, with flexibility for personal commitments. Afternoons could involve code reviews, documentation, or exploring new technologies to improve system performance.

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🎯 Who Element84 Is Looking For

  • Strong background in AI/ML engineering with experience in deploying models in production, particularly in geospatial or remote sensing contexts.
  • Proficiency in cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code (Terraform, CloudFormation) for building scalable data processing pipelines.
  • Experience with geospatial data formats (GeoTIFF, NetCDF) and libraries (GDAL, Rasterio, Xarray) is highly preferred.
  • Excellent problem-solving skills and ability to work collaboratively in a remote-first environment, with strong communication skills.

📝 Tips for Applying to Element84

1

Tailor your resume to highlight specific projects involving AI/ML in geospatial or aerospace domains, quantifying impact (e.g., accuracy improvements, scalability).

2

Include a portfolio or links to GitHub repos showing your work on geospatial data processing or AI/ML pipelines.

3

Mention any experience with Earth science data (e.g., NASA, NOAA) or familiarity with Element84's past projects (e.g., Cumulus, MAAP).

4

In your cover letter, explicitly align your skills with their values: 'We Invest in Each Other, We are Reliable, Our Work Benefits our World'.

5

Since it's remote, emphasize your ability to work asynchronously and communicate effectively across distributed teams.

✉️ What to Emphasize in Your Cover Letter

['Your passion for using AI/ML to solve environmental or aerospace challenges.', 'Specific experience with cloud-based geospatial processing, especially with tools like AWS, Docker, and Kubernetes.', "How you embody Element84's values, particularly reliability and investing in team success.", 'Your adaptability to remote work and collaborative problem-solving.']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Explore Element84's website and blog posts about their projects like Cumulus (NASA's cloud-based data management system) and MAAP (Multi-Mission Algorithm and Analysis Platform).
  • → Read about their involvement in open-source geospatial tools and contributions to the community.
  • → Look into their team culture and any recent news about their work in aerospace or AI.
  • → Understand their stance on remote work and how they support distributed teams.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Describe a time you designed an AI/ML pipeline for geospatial data. What challenges did you face with data volume or resolution?
2 How would you approach integrating a new ML model into an existing cloud-based data processing system?
3 What experience do you have with containerization and orchestration (Docker, Kubernetes) in a remote sensing context?
4 How do you ensure the reliability and reproducibility of your ML models in production?
5 Why are you interested in working at Element84, and how do you align with our mission and values?
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⚠️ Common Mistakes to Avoid

  • Submitting a generic application without mentioning geospatial or aerospace experience.
  • Underemphasizing cloud infrastructure skills; they are crucial for this role.
  • Not showcasing any tangible AI/ML project outcomes or real-world applications.

📅 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 Element84!

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