Full Stack Data Scientist

Full Stack Data ScientistCompany:The Boeing CompanyAt 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 programsDevelop and maintain data pipelines, workflow orchestration solutions, and data integration services that support analytics and machine learning use casesBuild and support MLOps workflows for model training, experiment tracking, model registry, deployment, inference, monitoring, and lifecycle managementEngineer and operate infrastructure for traditional machine learning and generative AI workloads, including on-premises and hybrid model serving environmentsDeploy, administer, and optimize containerized applications and platform services using Kubernetes and associated ecosystem toolsCreate and maintain Helm charts, deployment templates, automation scripts, and reusable platform patterns for AI/ML applicationsImplement CI/CD and GitOps workflows to support secure, repeatable, and observable software and model delivery processesConfigure and support observability capabilities including metrics, logs, traces, dashboards, alerting, and reliability reportingApply DevSecOps principles across application and infrastructure delivery, including certificate management, secrets handling, access control, least privilege, and defense-in-depth controlsSupport administration and integration of data storage technologies including relational, NoSQL, search, graph, object, and vector data platformsBuild and maintain secure container images and software supply chain controls, including vulnerability scanning and artifact managementCollaborate with data scientists and application teams to productionize models, improve runtime performance, and reduce friction in AI/ML development workflowsTroubleshoot complex platform, data, networking, deployment, and performance issues across distributed environmentsDevelop infrastructure-as-code and automation solutions to provision, configure, and manage platform resourcesContribute to architecture decisions, platform standards, technical documentation, operational runbooks, and engineering best practicesSupport incident response, root cause analysis, reliability improvement efforts, and continuous service optimizationTo meet U.S. export control compliance requirements, a “U.S. Person” as defined by 22 C.F.R. §120.62 is required. “U.S. Person” includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asyleeBasic Qualifications (Required Skills / Experience):Bachelor’s degree or higher in computer science, computer engineering, software engineering, data engineering, information technology, mathematics, or a related technical field3+ years of experience in software engineering, platform engineering, DevOps, site reliability engineering, data engineering, MLOps, machine learning infrastructure, or a related technical discipline3+ years of experience developing software and automation solutions using Python3+ years of experience building, deploying, operating, and orchestrating containerized applications using tools such as Docker, Podman, Buildah, and Kubernetes3+ years of experience designing or supporting CI/CD pipelines and modern software delivery practices3+ years of experience working with data pipeline orchestration tools, building production data workflows, databases, or data platforms in production environments3+ years of experience implementing monitoring, logging, alerting, or observability solutions for production systems3+ years of experience working in Linux-based environments and troubleshooting distributed systemsPreferred Qualifications (Desired Skills / Experience):Master’s in Computer Science, Machine Learning, Applied Mathematics, Computer Engineering, Software Engineering, Artificial Intelligence, Physics, or a closely related technical fieldExperience applying foundational cybersecurity practices in application or infrastructure engineering environmentsExperience 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 managementExperience 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 technologiesExperience with Kubernetes-based platform engineering, containerized application deployment, Helm, enterprise Kubernetes distributions, and GitOps/CI/CD workflows using tools such as ArgoCD and GitLabExperience 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 automationExperience 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 enforcementExperience 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 architecturesKnowledge 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 solutionsTypical 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, Master+3 years' related work experience, 6years' related work experience, etc.)Conflict of Interest:Successful candidates for this job must satisfy the Company’s 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 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: $137,700-$186,300Language Requirements:Not ApplicableEducation:Bachelor's Degree or EquivalentRelocation:Relocation assistance is not a negotiable benefit for this position.Export Control Requirement:This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a “U.S. Person” as defined by 22 C.F.R. §120.62 is required. “U.S. Person” includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee.Safety Sensitive:This is not a Safety Sensitive Position.Security Clearance:This position does not require a Security Clearance.Visa Sponsorship:Employer will not sponsor applicants for employment visa status.Contingent Upon Award ProgramThis position is not contingent upon program awardShift:Shift 1 (United States of America)Stay safe from recruitment fraud! The only way to apply for a position at Boeing is via our Careers website. Learn how to protect yourself from recruitment fraud - Recruitment Fraud WarningBoeing 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.EEO is the lawBoeing EEO PolicyRequest an AccommodationApplicant PrivacyBoeing Participates in E – VerifyE-Verify (English) E-Verify (Spanish) Right to Work Statement Right to Work(English) Right to Work(Spanish)SummaryLocation: USA - Seattle, WA; USA - Arlington, VAType: Full time