Cisco is building an AI Platform Team to create the next-generation foundation for intelligent, secure, and scalable AI solutions across Cisco's ecosystem, addressing challenges in LLM capabilities, agentic frameworks, data pipelines, and trustworthy AI deployment.
Requirements
- Strong background in ML engineering, deep learning, and statistical modeling; experience building scalable ML solutions.
- In-depth knowledge of Transformer-based architectures (e.g., GPT) and training/fine-tuning large-scale models; exposure to Agentic frameworks.
- Data preprocessing (tokenization, stemming, lemmatization), handling ambiguity and context, and transfer learning for domain/language adaptation.
- Skilled in data annotation strategies and model evaluation with appropriate metrics (LLM as judges, RAG and Agent evaluations and so on).
- Experience deploying LLMs to production with efficiency, reliability, and scalability.
- Applied LLMs in chatbots, content generation, semantic search, and related use cases.
- Proficiency in programming languages such as Python or R, and experience with machine learning libraries (e.g., TensorFlow, PyTorch)
Responsibilities
- Model Training, and Evaluation: This encompasses the complete cycle of training, fine-tuning, and validating language models.
- You will be designing and adapting LLMs for use in virtual assistants, automated chatbots, content recommendation systems, etc.
- You will come up with evaluations for the solutions and iterate on improvements.
- Algorithm Development for Enhanced Language Understanding: Focusing on the development or refinement of algorithms to improve the efficiency and accuracy of language models and understanding and generation tasks.
- Experimentation with Emerging Technologies and Methods: Actively exploring new technologies and methodologies in language model development, including experimental frameworks and software tools.
Other
- BA/BS with 3+ years or MS in machine learning, proven project portfolio.
- Excellent problem-solving and communication skills, with the ability to explain sophisticated concepts to non-technical partners
- Proven experience to work collaboratively in multi-functio
