The Boeing Company Mobility, Surveillance, and Bombers (MS&B) division is seeking to design, build, validate, and deploy AI-enabled analytics solutions, productivity enablers, and digital capabilities to support engineering products and manufacturing processes.
Requirements
- Demonstrated experience choosing analytic methods, defining algorithms, validating models, and deploying them into deployed systems.
- Determining, defining, and deploying descriptive, predictive, or prescriptive analytic solutions that support the research, design, development, test, and evaluation of company products, productivity enablers, or processes.
- Strong data science skills in Python and experience with at least one industry-standard language or framework (e.g., Java, C-Sharp, Go)
- Solid understanding of model evaluation metrics, validation techniques, and quality assurance for analytic outputs.
- Familiarity with unit/integration testing, code review, CI/CD aligning with software best practices.
- Practical experience with AI/ML frameworks and data tooling (TensorFlow, PyTorch, scikit-learn, pandas, NumPy).
- Experience deploying services on cloud platforms (AWS/Azure/GCP), containerization (Docker), and orchestration (Kubernetes) or equivalent on-prem runtime environments.
Responsibilities
- Lead the end-to-end delivery of AI/ML-enabled analytics components such as requirements translation, data preparation, model design, implementation, testing, deployment, and monitoring.
- Select and apply best-fit analytic methodologies (statistics, machine learning, optimization, simulation) and define algorithms to meet engineering objectives.
- Implement robust data engineering and feature preparation pipelines (cleansing, conditioning, transformation, handling missing data, feature extraction).
- Build quality services and APIs to operationalize models; ensure scalability, observability, security, and maintainability.
- Validate and verify models using standardized evaluation procedures; perform calibration, uncertainty estimation, robustness, and regression testing.
- Apply modern AI techniques (including deep learning and LLM methods where appropriate), and integrate tooling for model fine-tuning, prompt engineering, or retrieval-augmented workflows as required by use cases.
- Implement MLOps practices: CI/CD for models and analytics, model versioning, automated testing, and controlled model rollouts.
Other
- This position is expected to be 100% onsite.
- The selected candidate will be required to work onsite in Oklahoma City, OK.
- This position requires the ability to obtain a U.S. Security Clearance for which the U.S. Government requires U.S. Citizenship.
- An interim and/or final U.S. Secret Clearance Post-Start is required.
- Strong communication and collaboration skills; experience working in cross-functional teams.
