Top AI & Machine Learning Jobs

Lead an engineering data science team to define, develop, and deploy predictive and prescriptive analytics, ML algorithms, LLM solutions, and visualizations. Manage staff, suppliers, and stakeholder relationships while executing technical strategies and process improvements for product and manufacturing development.

Lead Boeing’s enterprise AI governance program by designing intake, review, risk-tiering, approval, and escalation workflows. Develop AI policies, standards, documentation, training, metrics, and executive reporting. Conduct AI risk assessments, evaluate vendor and generative AI systems, monitor regulatory requirements, and coordinate with engineering, legal, compliance, cybersecurity, and business stakeholders to ensure responsible, auditable AI adoption.

Leads end-to-end architecture for scalable, secure AI solutions supporting Boeing’s supply chain. Designs hybrid cloud and on-premises data, AI, and analytics architectures; translates business needs into technical solutions; and guides modeling, ontology, orchestration, deployment, monitoring, governance, and visualization. Partners with business leaders, product managers, engineers, data scientists, and platform teams to develop machine learning, generative AI, agentic AI, deep learning, and decision-support capabilities.

Leads business intelligence model, dashboard, metric, and report development for compliance analytics. Uses SQL, Python, R, VBA, statistical programming, predictive modeling, and advanced analytics to identify risks, trends, anomalies, and root causes. Translates complex data into actionable recommendations, communicates insights to technical and executive stakeholders, and supports compliance strategy and risk mitigation.

Design, build, and deploy machine learning solutions in distributed systems; collaborate with engineers and subject-matter experts; evaluate and improve models; ensure data security and compliance; communicate insights to stakeholders; mentor junior data scientists.

Lead data science efforts for a defense program onsite in Hazelwood, MO. Define data requirements, build analysis systems, design/deploy ML models, collaborate with engineers and SMEs, mentor junior scientists, ensure security/compliance, and communicate results to stakeholders while improving models and establishing best practices.

Design and build distributed data systems for analysis and ML; lead and mentor data scientists; implement, deploy, and improve ML models (including deep learning and LLMs); ensure data quality, security, and compliance; integrate models into customer on‑prem and cloud environments; communicate insights to stakeholders and drive best practices.