AIML Software Engineer Geospatial

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Overview

The AIML Software Engineer Geospatial at Leidos will be responsible for developing and implementing advanced artificial intelligence and machine learning algorithms applicable to geospatial data analysis. The engineer will collaborate with cross-functional teams to design and optimize solutions that enhance data processing capabilities, driving innovation in geospatial applications. This role requires a combination of technical expertise in software engineering, geospatial analysis, and a deep understanding of AIML methodologies. The ideal candidate will possess a strong analytical mindset and a passion for leveraging technology to solve complex problems in the geospatial domain.

Job Responsibilities

• Design, develop, and implement AIML algorithms tailored for geospatial data analysis.
• Collaborate with data scientists and geospatial analysts to refine project requirements and objectives.
• Perform data preprocessing, feature extraction, and model training on large datasets to facilitate accurate predictive modeling.
• Optimize algorithms for performance and scalability across different computing environments.
• Document code, methodologies, and processes to ensure maintainability and knowledge transfer.
• Participate in code reviews and contribute to best practices in software development.
• Stay abreast of industry trends and emerging technologies related to AIML and geospatial analysis.

Qualifications

• Bachelor's degree in Computer Science, Geospatial Science, or related field; Master’s degree preferred.
• 3+ years of experience in software development, particularly with AIML applications.
• Proficiency in programming languages such as Python, Java, or C++.
• Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with geospatial technologies and libraries (e.g., GDAL, ArcGIS, QGIS).
• Familiarity with cloud computing services (e.g., AWS, Azure) and containerization tools (e.g., Docker, Kubernetes).
• Excellent problem-solving skills and attention to detail.

Technologies & Tools

The AIML Software Engineer Geospatial will utilize a variety of technologies and tools including, but not limited to, programming languages such as Python and Java, machine learning libraries like TensorFlow and PyTorch, as well as geospatial software like ArcGIS and QGIS. Familiarity with data processing tools, cloud services like AWS, and container orchestration tools such as Kubernetes will be essential for optimizing workflows and deploying solutions efficiently.

Ideal Candidates

Ideal candidates for the AIML Software Engineer Geospatial position at Leidos are individuals who possess a strong analytical mindset paired with creativity and innovation. They should demonstrate adaptability in a fast-paced environment, effectively communicate complex concepts to diverse audiences, and work collaboratively within multidisciplinary teams. A commitment to continuous learning, coupled with the ability to navigate and solve complex challenges in data analysis, makes a candidate not only effective but also integral to the success of the projects undertaken.