At a Glance
- Tasks: Design and deliver cutting-edge AI solutions for complex enterprise environments.
- Company: Join a forward-thinking tech company leading in AI innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with potential for career advancement.
- Why this job: Be at the forefront of AI technology and make a real impact.
- Qualifications: 10-15 years of experience in Python and Generative AI applications.
The predicted salary is between 63000 - 77000 £ per year.
Permanent / Fixed term contract/ Contract Inside IR35
Contract Length: Initial 6-12 months with possible extensions
Start Date: Immediate preferred
Location Requirement: Onsite (3 days per week in the office and 2 days remote)
Applicants legally authorized to work in the United Kingdom without the need for current or future visa sponsorship preferred
Experience: Minimum 10-15 years
We are seeking a Generative AI Scientist to design and deliver agent‑based, AI‑enabled solutions integrated into complex enterprise environments. This is a hands‑on engineering role, focused on building production‑grade AI systems that move beyond experimentation into scalable, secure, and measurable outcomes for our clients.
What You’ll Be Doing
- Build Agent‑Based AI Systems
- Design and develop multi‑agent orchestration workflows (supervisor / sub‑agent patterns)
- Implement multi‑step, asynchronous pipelines to solve complex enterprise problems
- Integrate AI workflows into client systems via secure, well‑designed APIs
Develop LLM‑Enabled Applications
- Deliver end‑to‑end LLM‑powered features in production environments
- Design effective prompting strategies and context management
- Implement structured outputs, validation, and safety guardrails, aligned to responsible AI principles
Design Retrieval & Data Pipelines (RAG)
- Build and optimise retrieval‑augmented generation (RAG) pipelines
- Work with: Vector search and similarity retrieval
- Search and indexing systems
- Embeddings and content storage
- Caching strategies for performance and scalability
Backend & Platform Engineering
- Develop Python‑based backend services (APIs, integrations, orchestration layers)
- Apply strong engineering discipline across testing, observability, and error handling
- Contribute to reusable assets and patterns within UST’s AI ecosystem
Cloud‑Native Delivery (AWS)
- Deploy and operate scalable solutions on AWS
- Ensure best practices across: Security and IAM, Reliability and performance, CI/CD and environment management
What We’re Looking For
- Strong experience in Python backend engineering
- Hands‑on delivery of Generative AI / LLM‑based applications
- Experience with: Agent frameworks (e.g. LangChain, LlamaIndex, or similar)
- Experience with: Retrieval‑based systems (RAG, vector databases, embeddings)
- Experience with: APIs, microservices, and asynchronous workflows
- Experience deploying production systems in AWS environments
Nice To Have
- Experience with multi‑agent architectures
- Exposure to productionising AI systems at scale
- Knowledge of data pipelines, search infrastructure, and platform engineering
Generative AI Scientist (Lead II - ML Engineering) in London employer: UST
As a Principal Data Engineer at our company, you will thrive in a dynamic and innovative work culture that prioritises technical excellence and continuous learning. With opportunities for mentorship and collaboration across diverse teams, you will play a pivotal role in shaping the future of our cloud-scale data platform while enjoying the flexibility of a hybrid work environment in Nottingham or London. We are committed to fostering your professional growth and providing a supportive atmosphere where your contributions directly impact our success.
StudySmarter Expert Advice🤫
We think this is how you could land Generative AI Scientist (Lead II - ML Engineering) in London
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like UST.
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We think you need these skills to ace Generative AI Scientist (Lead II - ML Engineering) in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at UST, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at UST. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at UST
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at UST!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
