Proprietary Program Systems Engineering Technician (Experienced or Lead)

Proprietary Program Systems Engineering Technician (Experienced or Lead)

Company:

The Boeing Company

Boeing Defense, Space & Security (BDS) is looking for MSOSA Model Technicians to join our Systems Engineering Integration & Test (SEIT) team in Hazelwood, MO.

The MSOSA (Magic Systems of Systems Architect) Model Technician will be responsible for overseeing model development, validation, deployment, monitoring, and retirement activities for MSOSA models. This role ensures model performance, reliability, explainability, and compliance with internal policies and external regulations. The MSOSA Model Technician will partner with data scientists, engineers, product owners, and business stakeholders to translate business needs into robust, auditable models and sustainable operational processes.

Our teams are currently hiring for a broad range of experience levels including Experienced or Lead Level MSOSA Model Technicians.

Position Responsibilities

• Lead end-to-end model lifecycle management for MSOSA models: scoping, design, development oversight, testing, deployment, monitoring, and retirement.
• Define and maintain model governance standards, documentation requirements, and approval workflows.
• Coordinate model validation and independent review activities; ensure timely remediation of findings.
• Implement and oversee model performance monitoring, drift detection, and anomaly response processes.
• Ensure model explainability, interpretability, and reproducibility; maintain model lineage and version control.
• Manage cross-functional teams (data scientists, ML engineers, software engineers, DevOps) to operationalize models reliably and securely.
• Establish and track key model performance indicators (KPIs) and service-level objectives (SLOs).
• Ensure compliance with relevant regulations, industry best practices, and internal policies (e.g., data privacy, fairness, risk management).
• Facilitate stakeholder communication and provide regular reporting to business owners and leadership.
• Drive continuous improvement of modeling practices, tooling, and automation (CI/CD for models, ML Ops).
• Support model risk assessments and integrate model controls into enterprise risk frameworks.

This position is expected to be 100% onsite. The selected candidate will be required to work onsite.

Travel may be required up to 10% of the time; Domestically and/or internationally depending on business needs.

This position requires an active U.S. Secret Security Clearance (U.S. Citizenship Required). (A U.S. Security Clearance that has been active in the past 24 months is considered active)

Basic Qualifications (Required Skills/Experience)

• Associate’s degree and 3 or more years of related work experience or an equivalent combination of education and experience
• Knowledge of model risk management and regulatory expectations relevant to the industry.
• 3+ years’ experience using excellent communication skills and ability to translate complex technical concepts for business stakeholders.

Preferred Qualifications (Desired Skills/Experience)

• Associate’s degree and 6 or more years of related work experience or an equivalent combination of education and experience
• Proven ability to lead cross-functional teams and manage multiple projects simultaneously.
• Experience specifically with MSOSA model frameworks or domain-specific MSOSA applications.
• Familiarity with explainability tools (SHAP, LIME), fairness and bias testing, and adversarial robustness testing.
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps platforms.
• Prior experience in regulated industries (aviation, finance, healthcare, defense, etc.).
• 5+ years of experience in statistical modeling, machine learning, or related analytics roles; 2+ years in a model governance, model management, or ML Ops role preferred.
• Strong understanding of model development methodologies, validation techniques, and lifecycle management.
• Hands-on experience with model deployment and monitoring tools, version control, and orchestration frameworks (e.g., Docker, Kubernetes, MLflow, CI/CD pipelines).
• Experience with Python and common ML libraries (scikit-learn, TensorFlow, PyTorch, XGBoost) and data-processing tools (SQL, Spark).

Typical Education & Experience  

Experienced (Level 3)

Education/experience typically acquired through advanced education (e.g. Associate) and typically 3 or more years' related work ex