AI Machine Learning Engineer III

Meet The Team

Cisco Webex is the world's #1 business collaboration and customer engagement platform. It is used across all industries in the world being used to support governments, business, education, and more, including use by 85% of Fortune 500 business.

The workplace of the future will be powered by AI, and we, Collaboration AI, is the team responsible for building AI/ML intelligent experiences within Cisco’s Webex portfolio. The team is made up of multiple major AI fronts to enrich the collaboration use cases. This, in the order of processing pipeline, includes audio codec technologies, automatic speech recognition (ASR), text-to-speech (TTS), natural language processing (NLP) using and training LLMs and beyond, and gen‑AI evaluation methodologies, both metric-based and subjective testing.

In addition, videos are empowered via computer vision (CV) and additional contextual information by employee graphs, and much more.

We aim to build the next-generation AI solutions in collaboration software, devices, and APIs - from digitizing the in‑meeting, enhancing distributed team efficiency and improving all aspects of people connection.

In this role, you will be responsible for conducting applied NLP research to advance our Language AI features. This includes, but not limited to, hierarchical summarization, internationalization, evaluation of generated texts, human alignment, and more fundamentally, a crucial set of techniques that can utilize the existing pre‑/mid‑/post‑trained LLM model checkpoints to the best extent, by, for instance, fine‑tuning, adaptation, model surgery/editing, and reinforcement learning to customize models for the business need, for cloud, on‑prem, and on‑device deployment.

Your duties will include innovating and employing cutting‑edge technologies with the consideration of practical product launch, which concerns optimization of performance, scalability, safety, reliability, and measurable generation quality. Staying up to date with the latest advancements in AI and machine learning (ML) is expected, as is suggesting how new technologies might be implemented. Addressing and resolving any modeling issues that arise from product applications will be an integral part of your responsibilities:

• Advance Collaboration AI's Language AI capabilities by researching, prototyping, and implementing next‑generation LLM technologies

• Conduct rigorous applied NLP research following systematic methodology: establish benchmarks, evaluate baselines, perform ablation studies, and deliver actionable recommendations

• Develop and evaluate NLP models that address specific business requirements

• Balance technical trade‑offs (performance, latency, cost, quality) to determine optimal production solutions

• Collaborate with product managers and stakeholders to translate research into production features

• Write production‑ready code with appropriate testing, documentation, and deployment considerations

• Pursue publication opportunities at top‑tier NLP and ML conferences

• Recent graduate or in your final year of studies toward a PhD, or Master’s degree with 3+ years of post‑graduation work experience in related fields. Relevant fields include Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related STEM program

• Strong foundation in machine learning and natural language processing, including familiarity with transformer architectures, common training schemes, and evaluation methodologies

• Proficiency in Python and experience with at least one deep learning framework

• Demonstrated NLP or ML research experience through publications, technical reports, thesis work, or significant contributions to related projects

• At least one NLP or ML research paper published in a top‑tier conference, such as ACL, EMNLP, ICLR, ICML, NeurIPS, etc.

• Experience in using cloud services such as AWS, Google Cloud Platform, and Azure, for model training and deployment.

• Experience writing production‑quality Python code including testing, documentation, and code review practices

• Familiar with LLM benchmarking methods and experience analyzing benchmark datasets

• Experience…