Applied AI Scientist (Recommender Systems)

JR United Kingdom; London; Hybrid; GBP 60,000 - 100,000; Full time

Job summary

An innovative startup focused on behavioural AI is seeking an Applied AI Scientist specializing in Recommender Systems. This exciting opportunity involves developing and implementing cutting-edge solutions that leverage reinforcement learning and generative AI. You'll work alongside industry experts to optimize machine learning models for performance in modern environments. If you're passionate about AI and eager to make a significant impact in the retail sector, this role offers a unique chance to contribute to groundbreaking projects in a collaborative, hybrid work environment.

Qualifications

• Hands-on experience implementing Recommender System solutions in a commercial context.
• Strong foundation in machine learning and deep learning algorithms.

Responsibilities

• Design and implement scalable Recommender Systems.
• Translate latest Recommender Systems advances into impactful solutions.

Skills

Recommender Systems

Machine Learning

Deep Learning

Python Programming

Performance Optimization

Education

MSc in Computer Science

MSc in Machine Learning

Tools

PyTorch

HuggingFace Transformers

Job description

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Applied AI Scientist (Recommender Systems), london

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Client:

Location:

london, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

3

Posted:

08.05.2025

Expiry Date:

22.06.2025

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Job Description:

Applied AI Scientist (Recommender Systems)

Algo1: London Area, United Kingdom

Hybrid: Minimum of 3 days per week in Central London office

About the job

We are a VC-backed startup focused on behavioural AI, currently in stealth mode. We are building for retail with a focus on Recommendation Systems, Reinforcement Learning and GenAI. We are looking for an Applied AI Scientist with deep experience in advanced Recommender Systems to work with our team of industry leading domain experts and engineers.

Areas of focus:

• Develop and implement: Design and implement scalable Recommender Systems.
• Solution development: Translate latest Recommender Systems advances into impactful solutions and products, from MVPs to fully deployed systems.
• Performance optimisation: Optimise machine learning models for performance in modern environments (e.g., distributed clusters, GPUs).

Requirements:

• Hands on experience: Implemented Recommender System solutions in commercial context.
• Education: MSc in Computer Science, Machine Learning, or a closely related field.
• Machine learning expertise: Strong foundation in machine learning and deep learning algorithms (e.g., deep neural networks, supervised/unsupervised learning, predictive analysis, forecast modelling).
• Programming proficiency: Excellent Python programming skills with experience in developing and debugging production-level code.
• Deep learning frameworks: Expertise with PyTorch and HuggingFace transformers.
• Generative AI: Strong practical understanding of LLMs and transformers.