Senior Geospatial AI/ML Engineer

As a Senior Geospatial AI/ML Engineer at Wherobots, your key responsibilities will include defining and maintaining the systems architecture for our ML and AI platform, collaborating with cross-functional teams on product development, and building technology around distributed geospatial model training. Additionally, you’ll work on integrating ML capabilities into WherobotsDB and Wherobots Cloud, while also contributing to open-source projects like Apache Sedona.

To be considered for the Senior Geospatial AI/ML Engineer role at Wherobots, you should have over 5 years of hands-on experience in implementing geospatial AI/ML pipelines and systems, proficient programming skills in Python and AI/ML frameworks like PyTorch or TensorFlow, alongside a solid understanding of cloud-deployed software architectures. Excellent collaboration and problem-solving skills are also paramount for this position.

The base salary range for the Senior Geospatial AI/ML Engineer role at Wherobots is competitive, ranging from $175k to $250k per year. However, the actual salary offered will depend on various factors such as the candidate's experience, skills, and work location.

Yes! Wherobots prioritizes flexibility and choice in working arrangements for most roles, including the Senior Geospatial AI/ML Engineer position. You can choose to work remotely or in the San Francisco office, depending on your preferences.

As a Senior Geospatial AI/ML Engineer at Wherobots, you will work on exciting projects involving the development of AI and ML algorithms for geospatial data, including scene classification, object detection, and the creation of geospatial foundation models. This will allow you to contribute significantly to real-world applications that impact various industries.

Wherobots provides a comprehensive benefits package to its full-time employees, which includes 100% coverage of medical, dental, and vision insurance, access to a 401(k) plan with employer match, and unlimited paid time off, making it a great place to work and thrive.

To prepare for the interview for the Senior Geospatial AI/ML Engineer position at Wherobots, ensure you review your past geospatial ML projects and be ready to discuss your experience with AI frameworks like PyTorch or TensorFlow. It’s also beneficial to understand the company’s tech stack and have questions about their current projects ready.

When answering this question, focus on a project that showcases your contributions to the geospatial AI/ML field. Include specific details about the problem you solved, the methods you employed, and the outcomes you achieved. Emphasize collaboration, technical skills, and the impact your work had on the company or clients.

Discuss your methodology for developing geospatial models, including data collection, preprocessing techniques, and the evaluation metrics you use. Explain any frameworks you prefer for training, such as PyTorch or TensorFlow, and highlight how you ensure the models are robust and scalable.

Reflect on past challenges like data quality issues or computational limitations. Explain how you tackled these issues using specific techniques or tools. Focus on problem-solving skills and adaptability, which are crucial traits for a Senior Geospatial AI/ML Engineer.

Explain your strategies for writing clean, modular code and your approach to documentation. Discuss practices like version control, testing, and code reviews that you implement to maintain software quality over time.

Share your knowledge of key geospatial algorithms, like image segmentation, object tracking, or spatial clustering. Illustrate your experience by discussing a specific application where you effectively employed these algorithms in a project.

Demonstrate your passion for continuous learning by sharing your favorite resources, such as leading journals, conferences, online courses, or open-source projects. Discuss how staying informed impacts your work and contributions at Wherobots.

Offer insights into your experience with cloud platforms like AWS or Azure. Discuss how you’ve utilized these technologies in building scalable solutions and any specific services you employed to enhance performance for geospatial applications.

Highlight the importance of teamwork in developing complex solutions. Share examples of how you’ve successfully collaborated with different teams, such as data scientists, software engineers, or product managers, and how it contributed to project success.

If applicable, discuss your contributions to open-source projects related to geospatial tech or AI/ML, such as Apache Sedona. Highlight what you learned from these experiences and how they enriched your skills as an engineer.

Emphasize the value you place on feedback and how you approach it as an opportunity for growth. Share an example of how feedback led to improvements in your work or how you adjusted your approach based on team insights.