Full Stack Data Scientist

Company:

At Boeing we innovate and collaborate to make the world better. Boeing Defense Space & Security (BDS) is seeking a Full Stack Data Scientist to join the Business Transformation organization in support of modernizing how BDS operates through artificial intelligence machine learning and advanced digital capabilities. This role will help build and scale the technical foundations that enable secure reliable and production-ready AI/ML solutions across the enterprise.

This position is ideal for a data scientist who brings a blend of data science data engineering MLOps platform engineering DevOps and site reliability engineering (SRE) experience. The selected candidate will help design implement secure and operate the infrastructure and platform services that support data pipelines model training model deployment observability and AI application delivery. The role will work across on-premises hybrid and cloud-based environments with a strong emphasis on enterprise-grade security resiliency traceability and operational excellence.

The full stack data scientist in this role will partner closely with data scientists software engineers data engineers cybersecurity teams infrastructure teams and business stakeholders to accelerate adoption of AI/ML capabilities within BDS. This includes enabling both traditional machine learning workflows and emerging generative AI use cases including support for on-premises model serving retrieval-augmented generation architectures and modern model lifecycle management practices. The role requires strong systems thinking and the ability to translate business and mission needs into scalable platform solutions.

The successful candidate will be expected to contribute both strategically and hands-on. They will help define best practices build reusable patterns automate infrastructure and delivery workflows improve platform reliability and support secure deployment of mission-relevant AI/ML systems. Depending on level this role may also provide technical leadership influence architecture decisions and mentor other data scientists across the organization.

This position offers the opportunity to shape the future of AI/ML enablement within Boeing BDS by building the secure and modern technical ecosystem needed to support transformation at scale.

Key Responsibilities:

• Design build deploy and operate secure scalable AI/ML platform capabilities for Boeing BDS users and programs
• Develop and maintain data pipelines workflow orchestration solutions and data integration services that support analytics and machine learning use cases
• Build and support MLOps workflows for model training experiment tracking model registry deployment inference monitoring and lifecycle management
• Engineer and operate infrastructure for traditional machine learning and generative AI workloads including on-premises and hybrid model serving environments
• Deploy administer and optimize containerized applications and platform services using Kubernetes and associated ecosystem tools
• Create and maintain Helm charts deployment templates automation scripts and reusable platform patterns for AI/ML applications
• Implement CI/CD and GitOps workflows to support secure repeatable and observable software and model delivery processes
• Configure and support observability capabilities including metrics logs traces dashboards alerting and reliability reporting
• Apply DevSecOps principles across application and infrastructure delivery including certificate management secrets handling access control least privilege and defense-in-depth controls
• Support administration and integration of data storage technologies including relational NoSQL search graph object and vector data platforms
• Build and maintain secure container images and software supply chain controls including vulnerability scanning and artifact management
• Collaborate with data scientists and application teams to productionize models improve runtime performance and reduce friction in AI/ML development workflows
• Troubleshoot complex platform data networking deployment and performance issues across distributed environments
• Develop infrastructure-as-code and automation solutions to provision configure and manage platform resources
• Contribute to architecture decisions platform standards technical documentation operational runbooks and engineering best practices
• Support incident response root cause analysis reliability improvement efforts and continuous service optimization

Basic Qualifications (Required Skills / Experience):

• Bachelors degree or higher in computer science computer engineering software engineering data engineering information technology mathematics or a related technical field
• 3 years of experience in software engineering platform engineering DevOps site reliability engineering data engineering MLOps machine learning infrastructure or a related technical discipline
• 3 years of experience developing software and automation solutions using Python
• 3 years of experience building deploying operating and orchestrating containerized applications using tools such as Docker Podman Buildah and Kubernetes
• 3 years of experience designing or supporting CI/CD pipelines and modern software delivery practices
• 3 years of experience working with data pipeline orchestration tools building production data workflows databases or data platforms in production environments
• 3 years of experience implementing monitoring logging alerting or observability solutions for production systems
• 3 years of experience working in Linux-based environments and troubleshooting distributed systems

Preferred Qualifications (Desired Skills / Experience):

• Masters in Computer Science Machine Learning Applied Mathematics Computer Engineering Software Engineering Artificial Intelligence Physics or a closely related technical field
• Experience applying foundational cybersecurity practices in application or infrastructure engineering environments
• Experience designing and operating end-to-end AI/ML data and MLOps platforms including data pipelines experiment tracking model registry deployment inference monitoring governance and lifecycle management
• Experience with production data engineering and analytics platforms using workflow orchestration tools Python data processing libraries and relational NoSQL graph search vector object and analytical data storage technologies
• Experience with Kubernetes-based platform engineering containerized application deployment Helm enterprise Kubernetes distributions and GitOps/CI/CD workflows using tools such as ArgoCD and GitLab
• Experience with observability reliability engineering and infrastructure automation including Prometheus Grafana Loki Tempo Mimir OpenTelemetry SLIs/SLOs incident response Terraform OpenTofu Pulumi Ansible shell scripting and Python automation
• Experience with secure containerization software supply chain security and DevSecOps practices including hardened container images SBOM generation image signing vulnerability scanning TLS certificate management secrets management RBAC least privilege and policy enforcement
• Experience supporting machine learning and generative AI workloads in enterprise environments including model serving model monitoring evaluation on-premises or hybrid LLM deployment and retrieval-augmented generation architectures
• Knowledge of AWS data and machine learning services and experience working in defense aerospace regulated or other high-assurance environments requiring secure reliable and auditable technical solutions

Typical Education / Experience:

Education/experience typically acquired through advanced technical education (e.g. Bachelor) and typically 9 or more years related work experience or an equivalent combination of technical education and experience (e.g. PhD 4 years related work experience Master 7 years related work experience 13 years related work experience etc.).

Typical Education/Experience:

Education/experience typically acquired through advanced technical education (e.g. Bachelor) and typically 5 or more years related work experience or an equivalent combination of technical education and experience (e.g. PhD Master3 years related work experience 6years related work experience etc.)

Conflict of Interest:

Successful candidates for this job must satisfy the Companys Conflict of Interest (COI) assessment process.

Relocation:

Relocation assistance is not a negotiable benefit for this position. Candidates must live in the immediate area or relocate at their own expense.

Travel:

Position may require travel up to 10% of the time.

Drug Free Workplace:

Boeingis 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.

Pay & Benefits:

At Boeing we strive to deliver a Total Rewards package that will attract engage and retain the top 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: $137700-$186300

Language Requirements:

Education:

Relocation:

Export Control Requirement:

Safety Sensitive:

Security Clearance:

Visa Sponsorship:

Contingent Upon Award Program

Shift:

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