
location_on3018, 10th Street North, Clarendon, Arlington, Arlington County, Virginia, 22201, United States
Are you looking for an opportunity to combine your technical skills with big-picture thinking to make an impact in aerospace and national defense? You understand your customer's environment and how to develop the right systems for their mission. Your ability to translate real-world needs into technical specifications makes you an integral part of delivering a customer-focused engineering solution.
As a systems engineer on our team, you have the chance to shape the development and upgrades of aerospace systems across multiple defense, civilian, and space domains by leading digital engineering and model-based systems engineering activities. Your customer will trust you to not only design and develop these systems but also evolve them with advanced technology solutions. On our team, you'll be able to broaden your skillset into areas like model-based design, model-based systems engineering, digital engineering, and technical analyses. Grow your skills by merging technical engineering expertise and model-based engineering to create digital engineering solutions that drive client missions.
Join us. The world can't wait.
Work model: On-site
3018, 10th Street North, Clarendon, Arlington, Arlington County, Virginia, 22201, United States
Arlington, Virginia
Skills: Digital Engineering, Model-Based Systems Engineering, Model-Based Design, Technical Analyses, Systems Integration, Ai/ml Platforms, Tensorflow, Pytorch, Keras, Scikit-Learn.
Education: Bachelor's degree in Data Science, Computer Science, or a STEM field required; Master's degree in AI, Machine Learning, Engineering, or related field preferred.
Experience applying AI/ML techniques to requirements and architecture development across the systems development lifecycle (SDLC). Experience performing analysis studies using AI/ML in modeling and simulation environments, such as predictive simulations or behavior analysis. Experience supporting aerospace systems engineering activities, incorporating AI-based methodologies for design optimization and predictive maintenance. Experience with scripting languages, such as Python, R, and Bash or PowerShell, for developing or automating AI processes. Knowledge of AI-based tools for exploring big data analytics and automation platforms that integrate AI capabilities, such as Ansible, Terraform, or CloudFormation. Possession of excellent verbal and written communication skills, especially in translating technical AI/ML concepts for varied stakeholders. Master's degree in AI, Machine Learning, Engineering, or related field. UML, SysML, and OMG Certified Systems Modelling Professional (OCSMP) Certification. Cloud+, AWS Solutions Architect Associate or Professional, Azure, or GCP Certification. CSEP or ASEP INCOSE Systems Engineering Professional Certification.