CX Machine Learning Engineer

Sourced from justjobs.com

Cisco's Customer Experience (CX) Engineering organization is hiring a Machine Learning Engineer to build and scale enterprise-grade AI/ML and Generative AI solutions powering Cisco IQ. The role spans the full ML lifecycle, including data pipelines, low-latency model serving, LLMOps infrastructure, and automated evaluation and observability. You will partner with product managers, data scientists, and software engineers to deliver secure, production-ready AI capabilities at enterprise scale.

• Architect, build, and scale AI/ML and Generative AI solutions including predictive models, RAG architectures, and agentic workflows
• Own robust data pipelines, low-latency model serving, and LLMOps infrastructure
• Establish automated evaluation and observability frameworks for model quality, accuracy, latency, and reliability
• Partner with product managers, data scientists, and software engineering teams to translate business needs into production-ready capabilities
• Drive responsible AI governance and technical excellence across the platform

• Bachelor's degree with 7+ years related experience, or Master's degree with 4+ years related experience
• Programming experience in Python and/or Java, including designing, developing, testing, and deploying production-grade software, APIs, or distributed services
• AI/ML experience developing, training, evaluating, and deploying models using PyTorch, TensorFlow, scikit-learn, XGBoost, or equivalent
• Generative AI/LLM development experience with LLMs, RAG, embeddings/vector databases, prompt engineering, AI agents, and LLM evaluation/observability tools such as LangChain/LangGraph, LangSmith, or OpenAI/Anthropic APIs
• Experience building data pipelines and data-intensive applications using SQL, Spark, Kafka, ETL/ELT frameworks, or cloud data platforms

• Hands-on experience with agentic AI applications, multi-agent workflows, tool/function calling, and context management
• Experience with LLMOps/MLOps and AI evaluation/observability tools such as LangSmith and MLflow
• Experience building cloud-native AI/ML applications on AWS or Google Cloud with Docker, Kubernetes, REST APIs, microservices, and CI/CD
• Proficiency with AI-assisted software engineering tools such as GitHub Copilot, Claude Code, or Cursor
• Ability to independently own complex technical problems, communicate effectively, and mentor other engineers