Applied AI Scientist (Recommender Systems)

ZipRecruiter; London; Hybrid; GBP 70,000 - 90,000; Full time

Job summary

A VC-backed startup in London is seeking an Applied AI Scientist specializing in Recommender Systems. You will design and implement scalable systems, translating the latest advances into impactful products. The role requires hands-on experience in commercial contexts and strong expertise in machine learning and programming, particularly in Python. Join a team of industry experts to innovate in the field of behavioural AI.

Qualifications

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

Responsibilities

• Design and implement scalable Recommender Systems.
• Translate advances into impactful solutions and products.
• Optimise machine learning models for performance.

Skills

Machine Learning

Deep Learning

Python

Education

MSc in Computer Science

Tools

PyTorch

HuggingFace

Job description

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.

Bonus points:

• Deep learning frameworks: Expertise with PyTorch and HuggingFace transformers.
• Generative AI: Strong practical understanding of LLMs and transformers.
• PhD in a related field.
• Reinforcement Learning knowledge.