Staff Machine Learning Scientist - AI Agent Systems

Zendesk; York and North Yorkshire; Hybrid; GBP 80,000 - 100,000; Full time

Job summary

A leading customer service software company in the United Kingdom is looking for a Staff Machine Learning Scientist to join their innovative team. In this role, you will design and implement cutting-edge AI solutions, leveraging machine learning and natural language processing. The ideal candidate should have a strong background in ML research and effective communication skills. This is an exciting opportunity to impact customer experience and work closely with a talented team in a hybrid work environment.

Benefits

Flexible working hours

Health and wellness benefits

Career development opportunities

Qualifications

• Proven record of Machine Learning or NLP research, ideally in industry.
• Knowledge of building deep learning neural network architectures.
• Ability to implement ideas from research literature into proof‑of‑concept models.
• Experience with LLMs and Prompt Engineering is a huge bonus.

Responsibilities

• Design and test novel AI solutions for real business problems.
• Own the full research projects from start to finish.
• Collaborate with product managers and AI engineers.
• Keep up with NLP and ML literature to find innovative solutions.

Skills

Machine Learning

Natural Language Processing

Deep Learning

Research literature implementation

Conversational AI

Team collaboration

Communication

Education

Degree in Computer Science, Engineering, or related field

Tools

Python

TensorFlow

PyTorch

Job description

A leading customer service software company in the United Kingdom is looking for a Staff Machine Learning Scientist to join their innovative team. In this role, you will design and implement cutting-edge AI solutions, leveraging machine learning and natural language processing. The ideal candidate should have a strong background in ML research and effective communication skills. This is an exciting opportunity to impact customer experience and work closely with a talented team in a hybrid work environment.