Data-Driven AI/ML Technology Solutions Engineer (Mid-Level and Senior)

Data-Driven AI/ML Technology Solutions Engineer (Mid-Level and Senior)

Company:

The Boeing Company

The Boeing Company Mobility, Surveillance, and Bombers (MS&B) division is currently seeking Data-Driven AI/ML Technology Solutions Engineers (Mid-Level and Senior) to design, build, validate, and deploy AI-enabled analytics solutions, productivity enablers, and digital capabilities that support engineering products and manufacturing processes. The role blends rigorous analytic method selection, model development and validation, and data science best practices to deliver reliable, maintainable systems that meet engineering and program needs.

Build your career by helping us develop cutting-edge AI/ML digital capabilities that drive innovation and efficiency across the MS&B division. You will be responsible for designing, developing, and implementing AI algorithms and models, ensuring data quality, and deploying scalable AI solutions into released tools and productivity enablers. This position will also support a Technical Lead Engineer (TLE) in advancing the use of AI/ML within the division.

In this position, you will leverage advanced technologies and programming paradigms to enhance and accelerate the discovery, evaluation, formulation, and deployment of innovative digital capabilities. By utilizing languages such as Python, Java, and C#, you will implement sophisticated algorithms and data structures that streamline processes, optimize performance, and facilitate the rapid iteration of analytical models, ultimately driving impactful outcomes across various projects.

We work in a casual but professional environment with multi-disciplined teams that take pride in developing, integrating, testing, and delivering innovative solutions and productivity enablers. There is long-term potential for career growth into technical leadership or management positions, and we value the curiosity, tenacity, and imagination our team members bring to our projects each day.

Key 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.
• Collaborate across engineering, product, and operations teams to align analytic solutions with engineering requirements and lifecycle processes.
• Investigate and recommend new analytic methodologies, tools, and technologies.
• Produce clear design documentation, interface definitions, test plans, and compliance artifacts; mentor team members and contribute to knowledge sharing.
• Ability to architect and implement proper DevSecOps to ensure proper security in the development lifecycle.

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.

Basic Qualifications (Required Skills/Experience):

• Bachelor of Science degree in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics or Chemistry
• 3 or more years of related experience
• 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.