Lead AI Scientist β€” LLM Systems & Experimentation

Lead AI Scientist β€” LLM Systems & Experimentation

Full-Time 80000 - 100000 Β£ / year (est.) No working from home possible
Experimentation Jobs

At a Glance

  • Tasks: Lead the design of evaluation frameworks and build scalable A/B tests for AI systems.
  • Company: Wise, a global tech company revolutionising money management.
  • Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
  • Other info: Dynamic work environment with a focus on collaboration and creativity.
  • Why this job: Join a pioneering team and shape the future of customer interaction with AI.
  • Qualifications: Experience in AI systems, strong analytical skills, and a passion for innovation.

The predicted salary is between 80000 - 100000 Β£ per year.

Wise is a global technology company building the best way to move and manage the world's money.

The Contact Automation team in London develops an intelligent system to power an automated Wise Assistant.

This system answers most customer questions within the chat interface and supports agents with complex issues.

Responsibilities include owning the design and evolution of evaluation frameworks for LLM-based systems, building scalable A/B tests to measure customer impact, and analysing

Lead AI Scientist β€” LLM Systems & Experimentation employer: Experimentation Jobs

Fyxer is an exceptional employer that fosters a dynamic work culture where innovation and autonomy are at the forefront. With rapid growth and a focus on applied AI, employees have unique opportunities for professional development and to make a significant impact in a fast-paced environment. Located in London, the company offers a collaborative atmosphere where team members can thrive and contribute to groundbreaking solutions in the tech industry.

Experimentation Jobs

Contact Details:

Experimentation Jobs Recruitment Team

We think you need these skills to ace Lead AI Scientist β€” LLM Systems & Experimentation

LLM Systems
A/B Testing
Evaluation Frameworks
Data Analysis
Customer Impact Measurement
Machine Learning
Natural Language Processing