Senior AI/ML Software Engineer

2 days ago

Fairfax Station, Virginia, United States Leidos Full time
Job Title:

Senior AI/ML Software Engineer

Job Summary:

Leidos is seeking an experienced Senior AI/ML Software Engineer to join our team. As a key member of our team, you will be responsible for developing innovative AI/ML solutions that process and analyze large geospatial datasets. You will work alongside other technical leaders to design, develop, and deploy AI/ML models and applications on cloud and high-performance computing platforms.

Key Responsibilities:
  • Lead the design, development, and implementation of AI/ML models to process and analyze large geospatial datasets.
  • 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.
  • Assist 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.
Requirements:
  • Bachelor's 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 like Jenkins, Docker, and Kubernetes.
  • Possess strong analytical and problem-solving abilities to troubleshoot complex technical issues and design effective solutions.
  • Possess effective communication and collaboration skills to work with Customers and cross-functional teams.
  • Must be able to prioritize tasks effectively, manage deadlines, and handle multiple projects simultaneously.
  • Excellent organizational skills and keen attention to detail.
  • Enthusiasm for learning and adapting to new technologies and methodologies.
  • US citizenship with a Secret clearance and ability to obtain a Top Secret clearance.
Preferred Qualifications:
  • PhD in a relevant field.
  • Recognized expert technologist with 10-15 years of 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).
Pay Range:

$122,200.00 - $220,900.00

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.

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