Top AI & Machine Learning Jobs

Develop detection, classification, image analysis, and AI/ML algorithms for security screening systems. Build data analysis, testing, validation, and model improvement tools; research emerging machine learning and deep learning methods; and collaborate with engineering teams to transition concepts from research into production. The role also requires technical documentation, stakeholder communication, and contributions to aviation and homeland security technologies.

The Data Science Intern will support enterprise reporting and analytics initiatives by gathering and cleaning data, conducting exploratory and statistical analysis, engineering features, and developing predictive AI/ML models. The role involves using Python, SQL, Snowflake, Tableau, and emerging AI technologies while collaborating with data engineers, analysts, IT teams, and business stakeholders to translate requirements into actionable, data-driven solutions.

Creates commercial AI-generated still images and videos from brief through final delivery. Develops visual concepts, storytelling, shot design, and finished work using generative AI alongside compositing, retouching, color grading, VFX, and other post-production techniques. Collaborates with creative and production teams, incorporates client feedback, guides junior artists, works directly with clients when needed, and helps establish evolving AI workflows and best practices.

Build and deploy AI-powered automations, internal tools, scripts, dashboards, and reporting systems across operations, growth, finance, fulfillment, supply chain, and customer experience. Work directly with the CEO and functional leaders to identify manual bottlenecks, develop end-to-end solutions, support forecasting and unit economics, and execute high-priority projects. The role requires strong ownership, analytical ability, technical fluency, and comfort operating across business functions in an intense onsite environment.

The Data Scientist develops advanced analytics, AI, machine learning, predictive models, and business intelligence solutions supporting pharmaceutical commercial strategies. Responsibilities include analyzing complex healthcare and longitudinal patient data, building scalable algorithms and automated analytics capabilities, integrating and governing cloud data, and communicating insights to technical and non-technical stakeholders. The role partners cross-functionally to support market intelligence, customer segmentation, targeting, promotional measurement, and data-driven decision-making across oncology, rare disease, and CNS franchises.

Conduct applied research on scalable optimization and resource-allocation algorithms for large communication networks. Apply machine learning, reinforcement learning, integer optimization, graph-based methods, and metaheuristics to improve solution quality and efficiency. Collaborate with software engineers to integrate algorithms into production aerospace networking systems, evaluate performance at realistic scale, publish research, support patent applications, and document novel methods.

Build and productionize applied AI and machine learning capabilities for Crucible, including LLM workflows, retrieval, tool use, orchestration, evaluation, and model-serving systems. Integrate optimization and forecasting models into reliable products, select models for constrained cloud, air-gapped, and edge environments, and establish technical standards for production AI. Collaborate with manufacturing, supply chain, data science, software engineering, and product teams to deliver measurable operational value.

Design and lead enterprise AI copilot architectures using Microsoft Copilot Studio, Azure AI Foundry, Power Platform, Microsoft 365, and Azure services. Define integration, data, security, governance, and compliance strategies; guide enterprise AI adoption; lead client workshops and architecture reviews; oversee delivery, testing, deployment, optimization, and rollout. Serve as a trusted advisor to executive stakeholders while mentoring delivery teams and establishing standards for prompts, connectors, orchestration, monitoring, and evaluation.

Build and operationalize production-grade AI applications, including AI agents, RAG pipelines, intelligent search, automated reporting, and decision-support tools. Integrate AI with enterprise systems, databases, and APIs using Python, C#/.NET, and TypeScript. Implement responsible AI guardrails, LLMOps monitoring, evaluation, security, and governance. Mentor developers, assess emerging AI technologies, and translate business needs into reliable technical solutions.

Leads the design and production deployment of data pipelines, data models, analytical applications, and machine learning solutions for aerospace manufacturing. Partners with IT, engineering, manufacturing, cybersecurity, and business stakeholders to deliver reliable, secure, traceable, and scalable analytics. Develops models for anomaly detection, forecasting, optimization, scheduling, and engine performance; establishes technical standards, testing frameworks, documentation, and governance; troubleshoots production issues; and mentors junior team members.