At a Glance
- Tasks: Use AI to create personalised product recommendations and develop cutting-edge ML systems.
- Company: Join a leading brand known for innovation and collaboration.
- Benefits: Enjoy discounts, competitive holidays, bonuses, and well-being support.
- Other info: Great career growth opportunities and supportive workplace culture.
- Why this job: Make a real impact with your skills in a dynamic tech environment.
- Qualifications: Experience in ML/AI, large datasets, and strong collaboration skills required.
The predicted salary is between 70000 - 90000 £ per year.
Responsibilities
- Use machine learning, recommender systems, and LLM‑powered conversational AI to deliver deeply personalised product and outfit recommendations.
- Design, develop, and productionise end‑to‑end ML and Gen AI systems, including retrieval, ranking, and LLM‑based components powering conversational experiences.
- Design and develop frameworks for evaluating LLM outputs (relevance, grounding, safety, user satisfaction) and integrate them into continuous experimentation pipelines.
- Partner cross‑functionally to deliver production‑ready solutions aligned to product and commercial goals.
- Contribute to best practices in model development, deployment, and monitoring across the team.
- Own ML/AI problems end‑to‑end – from framing and modelling through to production deployment, monitoring, and continuous improvement – delivering measurable business impact.
- Apply strong software engineering principles to build robust, scalable ML systems, taking responsibility for performance and reliability in production.
- Work with large‑scale datasets and distributed data processing (e. g., Spark) and with modern recommendation or personalisation systems (large‑scale retrieval and ranking architectures, real‑time inference, vector representations, approximate nearest neighbour search) at scale.
- Collaborate and communicate across Product, Engineering, and business teams.
Qualifications
- Proven track record of owning ML/AI problems end‑to‑end.
- Experience working with large‑scale datasets and distributed data processing (e. g., Spark).
- Experience with modern recommendation or personalisation systems at scale.
- Strong collaboration and communication skills across Product, Engineering, and business teams.
- Strong software engineering fundamentals and ability to build robust, scalable systems.
- Familiarity with LLM evaluation frameworks and continuous experimentation pipelines.
Benefits
- 20% colleague discount across all M&S products and third‑party brands after probation.
- Competitive holiday entitlement with the option to buy extra days.
- Discretionary bonus schemes based on objectives and company performance.
- Defined Contribution Pension Scheme and Life Assurance.
- Tailored induction and training programmes.
- Well‑being support: 24/7 virtual GP and PAM Assist.
- Industry‑leading parental, adoption and neonatal policies.
- Support for volunteering through a dedicated day off.
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Contact Details:
Marks and Spencer plc (UK) Recruitment Team
We think you need these skills to ace Data Scientist in City of Westminster
Machine Learning
Recommender Systems
Conversational AI
End-to-End ML Systems
LLM Evaluation Frameworks
Continuous Experimentation Pipelines
Software Engineering Principles
