AI/ML Software Engineer Geospatial

Leidos' National Security Sector is currently seeking an AI/ML Software Engineer to join our Spatial Solutions Division (SSD) in Decision Advantage Solutions Business Area. This is an exciting opportunity that allows you to develop solutions that are highly innovative and achieved through research and integration of industry best practices. You will have the opportunity to make significant contributions to our projects and gain hands-on experience in a cutting-edge technology environment.

Leidos' National Security Sector combines technology-enabled services and mission software capabilities in the areas of cyber, logistics, security operations, and decision analytics to support our defense and intel customers’ mission to defend against evolving threats around the world. Our team’s focus is to ensure our customers have the right tools, technologies, and tactics to keep pace with an ever-evolving security landscape and succeed in their pursuit to protect people and critical assets.

The ideal candidate will have experience working with geospatial data in an agile DevSecOps environment. You will collaborate closely with senior engineers and technical leaders to process and analyze geospatial datasets and contribute to the development and deployment of AI/ML models and applications on cloud and high-performance computing platforms. You will influence development of solutions that impact strategic project/program goals and business results.

Primary Responsibilities:

• Collaborate with senior engineers and cross-functional teams to design, develop, and deploy AI/ML models and applications
• Process and analyze large geospatial datasets (imagery, signals, video) to extract meaningful insights and improve model performance
• Optimize and tune AI/ML models for performance considering both computation efficiency and predictive accuracy
• Develop data preprocessing pipelines and feature engineering strategies tailored to geospatial data
• Conduct model evaluation and validation including performance metrics and error analysis
• Implement MLOps practices to streamline the machine learning lifecycle, including version control, automated testing, continuous integration, and deployment of models
• Monitor and maintain AI/ML models post-deployment, ensuring they continue to perform as expected and updating them as needed
• Participate in code reviews and provide constructive feedback to peers to maintain high coding standards
• Document model development processes, results, and best practices for knowledge sharing and reproducibility
• Stay updated with the latest advancements in AI/ML and geospatial analytics
• Assists in creating technical documentation and presentations to communicate findings and progress to stakeholders
• Implement hybrid-cloud solutions for scalable and efficient data processing and model deployment
• Ensure security best practices are integrated into the development lifecycle, including compliance with data protection regulations

Required Qualifications:

• Bachelor's degree in Computer Science, Data Science, Engineering or related field and 4+ years of experience in AI/ML engineering with a focus on model design, development, and deployment
• US citizenship is required with the ability to obtain TS/SCI w/poly. 
• Proficiency in programming languages such as Python, R, or Java
• Experience with cloud platforms such as AWS, Azure, or Google Cloud
• Familiarity with Agile DevSecOps practices and tools likes Jenkins, Docker, and Kubernetes
• Possess strong analytical and problem-solving abilities to troubleshoot complex technical issues and design effective solutions.
• Possess effective communication and be able to collaborate with Customers, and cross-functional teams, document technical processes, and present solutions to stakeholders.
• Must be able to prioritize tasks effectively, manage deadlines, and handle multiple projects simultaneously.
• Excellent organizational skills and keen attention to detail, with the ability to multitask and prioritize effectively in a fast-paced, dynamic work environment.
• Enthusiasm for learning and adapting to new technologies and methodologies

Preferred Qualifications:

• Experience with GIS tools and libraries (GDAL, Postgis, ArcGIS, QGIS)
• Experience with geospatial datasets and phenomenologies (EO, IR, SAR)
• Knowledge of machine learning frameworks and libraries (TensorFlow, PyTorch, Scikit-Learn)
• Agile-based knowledge and skill, including experience with Scrum Ceremonies and work management tools (e.g., (JIRA, Confluence).

Original Posting:

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.