Senior AI/ML Scientist in London

Senior AI/ML Scientist in London

London Full-Time 70000 - 90000 £ / year (est.) No working from home possible
Quilter plc

At a Glance

  • Tasks: Lead the development of innovative AI/ML solutions and enhance cutting-edge technologies.
  • Company: Join a forward-thinking AI Centre of Excellence in a dynamic environment.
  • Benefits: Enjoy competitive salary, private medical insurance, and flexible benefits.
  • Other info: Embrace a culture of diversity and innovation with excellent career growth opportunities.
  • Why this job: Make a real impact in AI while collaborating with top talent in the field.
  • Qualifications: Advanced degree in AI/ML and proven experience in delivering impactful solutions.

The predicted salary is between 70000 - 90000 £ per year.

Position AI Scientist – AI Centre of Excellence under Chief Operating Office (COO). Level: 4. Location: Southampton or London.

Responsibilities

  • AI/ML Solution Delivery: Hands on end-to-end development and deployment of both traditional and GenAI-based machine learning models, including discovery analytics, experimental design, model development, benchmarking, enhancement and deployment.
  • LLM & RAG Integration: Design and implement new Retrieval-Augmented Generation (RAG) pipelines and enhance existing frameworks, applying advanced techniques in data chunking/splitting, vectorization, knowledge graph representation (GraphRAG), and query retrieval and evaluation.
  • Model Evaluation & Prompt Engineering: Design and execute experiments to benchmark and evaluate model performance using both classical metrics (precision, recall, F-score) and GenAI-specific techniques (LLM-as-a-Judge, ROUGE, BERTScore). Develop and refine prompts to optimise GenAI model reasoning, accuracy, and overall effectiveness.
  • Cross-Functional Collaboration: Work closely with business partners, stakeholders, and technical teams (data engineering, platform engineering) to translate business requirements into impactful AI solutions.
  • Research & Innovation: Stay abreast of emerging tools, techniques, and best practices in LLMs, RAG, GenAI, model development & evaluation techniques and proactively apply new knowledge to drive innovation.

Qualifications

  • Advanced degree (MSc or PhD) in Machine Learning, Natural Language Processing, Artificial Intelligence, or a related field.
  • Proven track record of delivering AI solutions from research to production in real-world applications.
  • Strong foundation in machine learning algorithms and deep learning concepts including Neural Networks and Transformer-based architectures.
  • Knowledge in developing and deploying scalable models on Databricks, Azure, and AWS, leveraging tools such as FastAPI and Docker.
  • Proficient in model tracing and observability for LLM in production and implementing evaluation frameworks for model quality and reliability.
  • Strong understanding of software engineering best practices, including version control, testing, and CI/CD for production-ready AI systems.
  • Domain expertise in financial services or other regulated industries is highly desirable.
  • Strong experience in AI/ML research and development, specializing in deep learning-based NLP, Information Retrieval, and Generative AI.
  • Proven expertise in RAG/GraphRAG pipeline development and evaluation, including advanced retriever-reranker techniques.
  • Experience in building knowledge bases and ontologies is highly desirable.
  • Extensive experience in defining and implementing evaluation metrics for GenAI systems such as Recall, Precision, NDCG, LLM-as-a-Judge, BERTScore, BLEU score, and hallucination detection.
  • Provide mentorship and technical guidance to junior AI Scientists.
  • Strong proficiency in Python and experience with frameworks such as NumPy, Pandas, Scikit-learn, and modern Generative AI libraries (e.g., LangChain, LlamaIndex, Azure AI Foundry).
  • Hands-on experience with PyTorch, and leading LLM libraries such as Hugging Face, LangChain, LangGraph, and LlamaIndex.
  • Skilled in hypothesis formulation, defining evaluation metrics, conducting literature reviews, and building reproducible prototypes with critical outcome analysis.
  • Rapid Experimentation Mindset: Comfortable with a fail-fast, learn-fast approach, iterating quickly to validate ideas and accelerate innovation.
  • Exceptional problem-solving skills and a strong passion for innovation.
  • Excellent communication and collaboration abilities, thriving in cross-functional environments.

Inclusion & Diversity

We value diversity and strive to promote inclusivity in all aspects of our culture. We believe in equal opportunities for all, ensuring that no applicant encounters less favourable treatment based on anything but their skills, qualifications, experience, and potential. We celebrate the unique contributions of a diverse workforce and create a respectful, nurturing environment where every colleague can thrive. We are committed to treating all our job applicants fairly and with respect. Our people come from all kinds of backgrounds and have a wide range of expertise, so we welcome your application regardless of your beliefs, culture, gender identity, ethnicity, sexual orientation and or disability. Please contact the talent acquisition team if you need any reasonable adjustments made to the recruitment process, require information in an alternative format or have any questions around accessibility, we will try our very best to accommodate.

Benefits

  • Holiday: 182 hours (26 days)
  • Incentive Scheme: All employees are eligible to participate in incentive scheme, to incentivise business performance and the contribution.
  • Pension Scheme: A non-contributory company pension scheme that can be boosted through personal contributions.
  • Private Medical Insurance: Single cover as standard with options to increase cover to include your partner or children.
  • Life Assurance: 4x your salary.
  • Income Protection: 75% of salary, less state benefits, payable after 26 weeks of absence.
  • Healthcare Cash Plan: Jersey employees only.
  • Flexible benefits: UK employees can choose from a range of benefits and pay via a salary deduction.

Senior AI/ML Scientist in London employer: Quilter plc

As a Senior AI/ML Scientist at our AI Centre of Excellence, you will thrive in a dynamic and inclusive work culture that prioritises innovation and collaboration. Located in either Southampton or London, we offer competitive benefits including a generous holiday allowance, a non-contributory pension scheme, and private medical insurance, all designed to support your well-being and professional growth. Join us to be part of a forward-thinking team where your expertise in AI and machine learning will drive impactful solutions in a supportive environment that values diversity and encourages continuous learning.

Quilter plc

Contact Details:

Quilter plc Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior AI/ML Scientist in London

Tip Number 1

Network like a pro! Reach out to folks in the AI/ML space on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.

Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those involving GenAI and RAG pipelines. This is your chance to shine and demonstrate what you can bring to the table.

Tip Number 3

Prepare for interviews by brushing up on common AI/ML questions and case studies. Practice explaining your thought process clearly, as communication is key in cross-functional teams.

Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who are proactive!

We think you need these skills to ace Senior AI/ML Scientist in London

Machine Learning
Natural Language Processing
Generative AI
Deep Learning
Neural Networks
Transformer-based Architectures
Model Evaluation

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the Senior AI/ML Scientist role. Highlight your experience with AI solutions, model development, and any relevant projects that showcase your skills in machine learning and deep learning.

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with our mission at StudySmarter. Don’t forget to mention specific projects or achievements that relate to the job description.

Showcase Your Technical Skills:We want to see your technical prowess! Be sure to include your experience with tools like Python, PyTorch, and any frameworks you’ve used. Mention your familiarity with LLMs and RAG pipelines, as these are key for this role.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining the StudySmarter team!

How to prepare for a job interview at Quilter plc

Know Your AI Inside Out

Make sure you brush up on the latest trends and techniques in AI and machine learning, especially around LLMs and RAG. Be ready to discuss your hands-on experience with model development and deployment, as well as any innovative solutions you've implemented in past projects.

Showcase Your Collaboration Skills

Since this role involves working closely with various teams, prepare examples of how you've successfully collaborated with stakeholders and technical teams in the past. Highlight your ability to translate complex technical concepts into business-friendly language.

Prepare for Technical Questions

Expect to dive deep into technical discussions about model evaluation metrics and prompt engineering. Brush up on classical metrics like precision and recall, as well as GenAI-specific techniques. Be ready to explain your thought process behind designing experiments and evaluating model performance.

Demonstrate a Rapid Experimentation Mindset

This role values innovation and a fail-fast approach. Share examples of how you've iterated quickly on ideas and learned from failures. Show your passion for problem-solving and how you stay updated with emerging tools and best practices in the field.