Machine Learning Engineer (Geospatial)

*About Us*:
We are is at the forefront of a technological revolution in the agriculture sector. Through AI and satellite imaging, we aim to develop innovative tools that will redefine sustainable farming practices worldwide.

*Role*:
We are actively seeking a self-driven and experienced Machine Learning Engineer with a specialization in geospatial data. The candidate should be well-versed in computer vision algorithms, geospatial data engineering, MLOps, and have a solid background in software engineering.

*Key Responsibilities*:
1. Design, develop, and optimize machine learning models tailored for geospatial applications.
2. Implement computer vision algorithms such as VGG, ResNet, UNet, among others.
3. Process and manage extensive sets of satellite imagery data.
4. Ensure the efficient integration of ML models into our core products using MLOps best practices.
5. Utilize geospatial tools like Google Earth for enriched data analysis and visualization.
6. Establish and maintain scalable and reliable ML infrastructure in a standalone environment.
7. Apply software engineering best practices throughout the development lifecycle.
8. Oversee the full cycle of implementing ML models from research to deployment.

*Requirements*:
– Bachelor’s/Master’s degree in Computer Science, Data Science, Geospatial Science, or related fields.
– Proficiency in Python, especially with libraries like Plotly.
– Deep understanding of computer vision ML algorithms (e.g., VGG, ResNet, UNet).
– Demonstrated expertise in geospatial data engineering, particularly with platforms like Google Earth.
– Hands-on experience with satellite imaging and associated tools.
– Solid software engineering skills, with a history of implementing ML models in production environments.
– Excellent communication and problem-solving skills, with the ability to work autonomously.

*Nice to Have*:
– Experience in the agriculture domain.
– Familiarity with cloud platforms like AWS, GCP, or Azure.
– Published research in related fields.

*Benefits*:
– Competitive compensation package.
– Flexibility of remote work, fostering a work-life balance.
– Opportunity to be a pioneer in developing groundbreaking technology.
– Continuous learning and growth opportunities.

Ready to make waves in the agriculture tech space with Nile Link? Embark on this transformative journey with us!