AI Engineer

Job not on LinkedIn

🕒 June 18, 2025

🏢🏡 London – Hybrid

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

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Logo of Gradient Labs

Gradient Labs

WebsiteLinkedIn

1 - 10 employees

Founded 2023

🤖 Artificial Intelligence

🤝 B2B

☁️ SaaS

Artificial Intelligence • B2B • SaaS

Gradient Labs is an AI-driven company focusing on automating complex customer support interactions through its powerful AI agent named Otto. This agent is designed to handle intricate customer inquiries by learning from written procedures, offering seamless integration into existing support platforms. Gradient Labs aims to enhance customer service efficiency while maintaining high satisfaction rates, enabling businesses to automate significant portions of their customer support processes without the need for coding or complex setups.

📋 Description

• At Gradient Labs, we’re on a mission to make exceptional customer service the norm. • Our AI agent helps businesses handle even the trickiest, high-stakes customer support queries safely and effectively. • We’re a remote-first team but love getting together in London once a week to collaborate. • If you’re excited to tackle some of the hardest problems in AI and help shape the future of customer service, we’d love to hear from you. • As an AI Engineer at Gradient Labs, you would spend your time developing, evaluating, optimizing, and adding to the skills of our agent. • You’d keep up with the latest NLP and generative AI news and releases for prototyping and experimentation. • You would analyze customer queries and tickets to gain insights into patterns for further automation.

🎯 Requirements

• Excited to push the boundaries of what’s possible for autonomous agents that imitate human behaviour • Motivated to operate in a fast-pace environment, rather than longer research cycles • Can quickly summarise, replicate, and test ideas from research papers • Driven more by making an impact on the products they’re helping to build than academic research outcomes • Can persevere: many ideas you will experiment with will be ambiguous and might fail, a successful person in this role will find the strength to keep trying • Comfortable building with LLMs and have experience shipping LLM products to production (ideally have experience using Go)

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