Job Specifications
Engineering Manager, Machine Learning, Marketplace, Ecommerce, | 35 Million Users | London, Hybrid, 1 Day PW, Up to £140,000
About the Company
Our client is an extremely well know, digital marketplace focused on sustainable ecommerce. With over 35 million of active users globally, they’re redefining how people buy and sell second-hand fashion, aiming to make the future of style both circular and accessible.
The company has offices in UK, EU and US and experienced significant growth especially around the US market and now operates as part of a leading global e-commerce group. They pride themselves on fostering inclusivity, creativity, and innovation and values that extend to both their community and their teams.
The organisation champions diversity, equal opportunity, and flexible working. They offer a progressive benefits package designed to support wellbeing, learning, and work-life balance.
The Role of Engineering Manager, Machine Learning, Marketplace, Ecommerce, | 35 Million Users | London, Hybrid, 1 Day PW, Up to £140,000
Our client is seeking an experienced Machine Learning Engineering Manager to lead the reccomendation team. This person will drive innovation in how users find and engage with products through advanced machine learning models improving search relevance, personalisation, and conversion outcomes at scale.
You’ll lead a talented team of ML Scientists and collaborate cross-functionally with product, data, and engineering leaders to define and execute the ML roadmap for search. This is an opportunity to have tangible business impact while working with cutting-edge technology in NLP, computer vision, and multimodal retrieval.
Key Responsibilities for the Engineering Manager, Machine Learning, Marketplace, Ecommerce, | 35 Million Users | London, Hybrid, 1 Day PW, Up to £140,000
Lead, coach, and develop a team of ML Scientists, fostering a culture of experimentation, collaboration, and continuous learning.
Partner with Product, Data, and Engineering leaders to shape and deliver an actionable ML strategy that drives engagement, conversion, and growth.
Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation.
Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring).
Share insights and best practices across other ML teams, particularly in areas of recommendations, ranking, and multimodal representation learning.
Stay current with emerging research in NLP, CV, and multimodal retrieval; champion responsible AI principles; and communicate findings to both technical and non-technical audiences.
Requirements for the role:
7+ years of experience in applied machine learning with a proven track record delivering production models at scale.
At least 2 years of leadership experience managing ML Scientists or Engineers.
Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms).
Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow.
Strong grounding in experimental design, A/B testing, and the use of offline/online metrics to guide product strategy.
Excellent communication and stakeholder management skills, with the ability to bridge complex ML concepts for diverse audiences.
Familiarity with AWS and Databricks.
Experience with search infrastructure (e.g., OpenSearch or Elasticsearch).
What can they offer you?
Private health and mental wellbeing coverage, including access to counselling and coaching.
Salary of up to £140,000+Bonus & Benefits
25 days annual leave, plus additional company-wide rest days and volunteer leave.
Flexible hybrid working, with the option to work abroad for limited periods.
Generous parental, IVF, and carer leave policies.
Learning and development budgets for conferences, mentorship, and skills growth.
Pension matching, life insurance, and recognition for service milestones.