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Proprietary Program Systems Engineering Technician (Experienced or Lead)
Proprietary Program Systems Engineering Technician (Experienced or Lead)BOEING • Berkeley, Missouri, United States
Proprietary Program Systems Engineering Technician (Experienced or Lead)

Proprietary Program Systems Engineering Technician (Experienced or Lead)

BOEING • Berkeley, Missouri, United States
14 days ago
Job type
  • Permanent
Job description

Job Description

At Boeing, we innovate and collaborate to make the world a better place. We’re committed to fostering an environment for every teammate that’s welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.

Boeing Defense, Space & Security

(BDS) is looking for

MSOSA Model Technician s

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 experience or an equivalent combination of education and experience (e.g. Bachelor+1 years' related work experience, 5 years' related work experience, etc.).

Lead (Level 4)

Education / experience typically acquired through advanced education (e.g. Associate) and typically 6 or more years' related work experience or an equivalent combination of education and experience (e.g. Bachelor+4 years' related work experience, 8 years' related work experience, etc.).

Drug Free Workplace

Boeing is a Drug Free Workplace where post offer applicants and employees are subject to testing for marijuana, cocaine, opioids, amphetamines, PCP, and alcohol when criteria is met as outlined in our policies.

Employee Referral

Referral to this job is eligible for bonus to qualifying candidates.

Contingent Upon Award

This position is contingent upon award.

Total Rewards

At Boeing, we strive to deliver a Total Rewards package that will attract, engage and retain the top talent. Elements of the Total Rewards package include competitive base pay and variable compensation opportunities.

The Boeing Company also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work.

The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, and the applicability of collective bargaining agreements.

Pay is based upon candidate experience and qualifications, as well as market and business considerations.

Summary pay range (Experienced, Level 3) : $61,200 – $82,800

Summary pay range (Lead, Level 4) : $73,100 - $98,900

Applications for this position will be accepted until

Nov. 05, 2025

Export Control Requirements :

This position must meet export control compliance requirements. To meet export control compliance requirements, a “U.S. Person” as defined by 22 C.F.R. §120.15 is required. “U.S. Person” includes U.S. Citizen, lawful permanent resident, refugee, or asylee.

Export Control Details :

US based job, US Person required

Relocation

This position offers relocation based on candidate eligibility.

Security Clearance

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)

Visa Sponsorship

Employer will not sponsor applicants for employment visa status.

Shift

This position is for 1st shift

Contingent Upon Program Reward

The position is contingent upon program award

Equal Opportunity Employer :

Boeing is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military / veteran status or other characteristics protected by law.

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System Technician • Berkeley, Missouri, United States

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