Senior AI/ML Software Engineer

Description

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 Decision Advantage Solutions Business Area, Office of Technology, is seeking an experienced Senior AI/ML Software Engineer. As an AI/ML Software Engineer you will be required to develop solutions that are highly innovative and achieved through research and integration of industry best practices. The ideal candidate will have experience working with diverse data sets (ex. geospatial, radio frequency) data in an agile MLOps environment. You will work alongside other 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. You will resolve highly complex problems using significant application of technical knowledge, conceptualizing, reasoning and interpretation. You will interact daily with various technical resources across different vendors which are fulfilling technical requirements for the customer. This role offers the opportunity to make significant contributions to our projects and gain hands-on experience in a cutting-edge technology environment.

Primary Responsibilities:
*Lead the design, development, and implementation of AI/ML models to process and analyze large geospatial datasets, ensuring accuracy and scalability
*Create and use advanced machine learning algorithms to extract meaningful insights and patterns from geospatial data
*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
*Lead captures and their technical solutions (RFI & RFP responses) and program execution to ensure delivery of differentiated capabilities.
*Lead, participate in, and propose R&D and solution development efforts related for AI/ML solutions and associated technologies for successful deployment.
*Work with the program teams, Division leadership, and CTO organization to identify technology and solution roadmaps to improve mission enterprise capabilities and broad Leidos contribution in mission attainment resulting in increased contract growth and improved customer satisfaction.
*Partner with the Business Development team in supporting the shaping and development of technical solutions and industry relationships via new business reviews, white papers, customer shaping calls, and the Win Plan process for larger franchise opportunities.

Basic Qualifications:
*Bachelors degree in Computer Science, Data Science, Engineering or related field and 12+ years of prior relevant experience.
*7+ years of experience in AI/ML engineering with a focus on model design, development, and deployment
*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
*US citizenship with a Secret with the ability to obtain a Top Secret, SCI eligible

Preferred Qualifications:
*PhD in a relevant field
*Recognized expert technologist with 10-15 year experience in mission software solutions related to data science, machine learning, or other similar technology
*Experience with GIS tools and libraries (GDAL, Postgis, ArcGIS, QGIS)
*Experience with geospatial datasets and Phenomenology's (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).

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.

The Leidos pay range for this job level is a general guideline onlyand 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.