Cary, NC, 27512, USA
34 days ago
Principal AI Engineer
Role Value Proposition: As an AI & Data Science Engineer focused on enterprise AI platform development, you will play a pivotal role in architecting, designing, and implementing the core AI and machine learning (ML) infrastructure that underpins our next-generation business applications. You will collaborate with cross-functional teams--including enterprise platform and architecture team, data engineers, DevOps, and business stakeholders--to deliver solutions that are not only technically sound but also aligned with the strategic goals of the organization. Key Responsibilities: * AI Platform Capability Development: Design, develop, and manage scalable enterprise AI capabilities that support the AI platform. * Model Engineering: Design, train, and optimize machine learning and deep learning models for a variety of business use cases (e.g., SLM, computer vision, predictive analytics, recommendation systems). * Data Pipeline Engineering: Collaborate with data engineers to design and implement robust data ingestion, transformation, validation, and feature engineering pipelines tailored for AI/ML workloads. * Platform Integration: Enable seamless integration of AI capabilities into business applications and workflows through APIs, SDKs, and microservices. * Automation & MLOps: Develop and maintain CI/CD pipelines for ML models, ensuring automated testing, versioning, deployment, and monitoring in production environments. * Performance & Scalability: Optimize platform components for efficiency, scalability, and reliability using best practices in distributed computing, resource management, and cloud-native architectures. * Security & Compliance: Implement and advocate for security, privacy, ethical, and compliance best practices throughout the AI/ML platform and model development lifecycle. * Innovation & Research: Stay abreast of the latest trends and advancements in AI, ML, and platform engineering. Evaluate and prototype emerging technologies for inclusion in the enterprise platform. * Documentation & Knowledge Sharing: Produce clear technical documentation and participate in knowledge sharing to mentor team members and enable collaboration across the organization. Essential Business Experience and Technical Skills: Required: * Bachelor’s or Master’s degree in computer science, Data Science, Engineering, Mathematics, or a related field. A PhD is a plus. * 7+ years of experience in AI/ML engineering, GenAI, data science, or related roles. * Proficiency in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn, XGBoost, Hugging Face). * Strong software engineering skills with experience in Python (required). * Proven experience designing, developing, and deploying Generative AI (GenAI) solutions using large language models (LLMs) such as GPT, Llama, Claude, etc. * Experience with modern GenAI frameworks and libraries (e.g., LangChain, LlamaIndex, Hugging Face Transformers). * Familiarity with best practices for responsible AI, including data privacy, bias mitigation, and model monitoring. Preferred: * Experience with cloud platforms (AWS, Azure, GCP), containerization (Docker, Kubernetes), and orchestration tools. * Hands-on expertise with Retrieval-Augmented Generation (RAG) architectures, including integrating external data sources and vector databases to enhance LLM outputs. * Strong understanding of prompt engineering, fine-tuning, and evaluation of generative models for real-world applications. * Ability to build, optimize, and scale GenAI pipelines for tasks such as document Q&A, summarization, chatbots, and knowledge retrieval. At MetLife, we’re leading the global transformation of an industry we’ve long defined. United in purpose, diverse in perspective, we’re dedicated to making a difference in the lives of our customers. Equal Employment Opportunity/Disability/Veterans If you need an accommodation due to a disability, please email us at accommodations@metlife.com. This information will be held in confidence and used only to determine an appropriate accommodation for the application process. MetLife maintains a drug-free workplace.
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