🇺🇸 Machine Learning Engineer Full time

NICE is looking for an exceptional Machine Learning Engineer to join our team. As a Machine Learning Engineer, you will play a vital role in enhancing our contact center solutions through the development of prompt engineering as well as advanced algorithms and models. You will work in a collaborative team environment to explore and create solutions to industry problems using state-of-the-art large language models and generative AI. You bring to this team environment several years’ experience in machine learning as well as the curiosity and grit to see a project to delivery.

- Help diagnose and resolve issues with production prompts.
- Work with customer-facing stakeholders to capture customers' goals for generative AI applications.
- Conduct cutting-edge research and develop advanced ML algorithms and models, including domains outside generative AI such as cluster analysis and anomaly detection.
- Communicate research findings, technical concepts, and model recommendations effectively to technical and non-technical stakeholders.
- Build and fine-tune deep learning and machine learning models, with an emphasis on large language models.
- Stay informed of the latest advancements in LLM research and contribute to the development of our knowledge base.

- Minimum of 1 year of experience working with deep learning models using real-life (“industry”) data.
- Excellent proficiency in Python programming and one or more deep learning libraries
- Familiarity with best practices in prompt engineering.
- Experience with building and/or fine-tuning large language models as well as traditional machine learning models.
- Ability to develop and maintain good working relationships with cross-functional teams.

Additional Desired Skills and Experience
- Advanced degree in a STEM field: Data Science, Machine Learning, Computer Science, Math, Engineering, etc.
- Published research papers in the field of NLP or related areas.
- Experience with Python and at least one web app framework for prototyping, e.g., Streamlit or Flask.
- Experience working on international, globe-spanning teams.

TBD