Machine Learning Engineer

Job Description

****This role does not support Visa sponsorship****

NICE is looking for an exceptional MACHINE LEARNING SOFTWARE ENGINEER to join our team. As a MACHINE LEARNING SOFTWARE ENGINEER, you will play a vital role in enhancing our contact center solutions through the development of 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/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.

Responsibilities

• Conduct cutting-edge research and develop advanced ML algorithms and models.
• Build and fine-tune deep learning and machine learning models, with an emphasis on large language models.
• Communicate research findings, technical concepts, and model recommendations effectively to technical and non-technical stakeholders.
• Collaborate closely with business stakeholders to ensure model effectiveness and alignment with business objectives.
• Stay abreast of the latest advancements in LLM research and contribute to the development of our knowledge base.

Minimum Skills and Experience

• 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
• Experience with building and/or fine-tuning large language models, as well as traditional machine learning models.
• Strong research skills, with a proven track record of developing and implementing NLP algorithms.
• Excellent communication and presentation abilities.

Additional Desired Skills and Experience

• Advanced degree(s) in a STEM field: Computational Linguistics, Computer Science, Math, Engineering, etc.
• Experience deploying NLP models in production environments, ensuring scalability and performance.
• Published research papers in the field of NLP or related areas.
• Experience working on international, globe-spanning teams.