AI Engineer
The intern will be responsible for assisting with AI engineering tasks and projects. They will contribute to the development and implementation of artificial intelligence solutions.
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The intern will be responsible for assisting with AI engineering tasks and projects. They will contribute to the development and implementation of artificial intelligence solutions.
You will design, deploy, and manage intelligent AI agents and optimize complex RAG pipelines to automate customer tasks. Additionally, you will collaborate with product teams to translate requirements into technical specifications while ensuring robust backend architecture and system health.
The AI Engineer will translate complex business workflows and data into practical AI prototypes and solutions to enhance operational efficiency. They will collaborate with domain experts to design, build, and validate AI-enabled tools while ensuring adherence to security and quality standards.
You will build and deploy production-grade AI agents, intelligent systems, and automated workflows to solve complex business problems. The role involves collaborating with cross-functional teams to integrate AI solutions with backend services and third-party platforms.
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You will build and productionize AI systems, including LLM pipelines, agents, and real-time voice systems. Additionally, you will design evaluation suites and maintain backend infrastructure to ensure reliable, scalable AI products.
Design, develop, and deploy advanced AI and Generative AI solutions for healthcare technology platforms. Collaborate with software engineers to integrate models while ensuring compliance with regulatory standards like HIPAA.
You will design, develop, and deploy production-grade AI solutions to create measurable business value across Danaher operating companies. You will collaborate with multidisciplinary teams to industrialize AI and build scalable, reusable AI services and workflows.
Lead the engineering delivery of agentic AI solutions and intelligent workflows within the GTM technology stack. Design and optimize scalable AI architecture, including RAG systems and autonomous agents, while mentoring senior and mid-level engineering staff.
The AI Engineer will design and build agent-based workflows and FastAPI backend services to support a property-management platform. They are responsible for implementing RAG retrieval, managing AI cost controls, and ensuring the reliability of AI outputs through evaluation harnesses.
Architect and build LLM-based applications including copilots, chatbots, and AI agents while optimizing RAG systems. Drive LLMOps practices and own backend services for AI inference and orchestration.
Develop and deploy cutting-edge GenAI solutions while serving as a trusted technical advisor to customers. Collaborate cross-functionally with product and engineering teams to influence the product roadmap and present at industry conferences.
The role involves architecting and delivering scalable, production-grade Generative AI applications and enterprise-level AI platforms. You will lead technical discovery, define engineering standards, and partner with stakeholders to translate business requirements into robust technical solutions.
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Design, build, deploy, and optimize AI and generative AI solutions for healthcare platforms, including machine learning, multimodal LLMs, predictive analytics, natural language processing, and image processing. Integrate solutions with existing systems, manage model evaluation and monitoring, apply security and regulatory safeguards, and identify opportunities to automate workflows.
You will develop and maintain Python applications while managing AWS cloud infrastructure and CI/CD pipelines. The role involves improving system reliability and utilizing AI-assisted tools to deliver secure, high-quality software.
Design and ship end-to-end internal tools, services, and interfaces while integrating AI capabilities like LLMs and RAG. Collaborate across business teams to build scalable solutions that automate workflows and improve operational efficiency.
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Design, build, and deploy production-grade Generative AI and Agentic AI solutions to automate complex business processes. Collaborate with cross-functional teams to integrate LLM-powered applications with enterprise systems while ensuring scalability and performance.
Design and build LLM-powered analysis and classification pipelines, productionizing them as Go services. Collaborate with security researchers to translate attack patterns and risk signals into actionable detection logic.
The Lead Engineer will spearhead AI/ML development efforts, designing and deploying Agentic AI solutions within the ServiceNow ecosystem. They will also mentor a team of developers while managing complex projects across cloud platforms and big data environments.
You will act as the architect for internal AI systems, designing and deploying production-grade agents to automate workflows across sales, marketing, delivery, and finance. You are responsible for the entire lifecycle of these systems, from initial problem scoping to production maintenance and documentation.
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