At a Glance
- Tasks: Define engineering standards and drive adoption of cutting-edge AI technologies.
- Company: Global tech organisation focused on scaling enterprise AI solutions.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic role with excellent career progression in a collaborative environment.
- Why this job: Join a team shaping the future of AI with innovative projects and impactful solutions.
- Qualifications: Deep experience in Python, AWS, and hands-on with LangChain and RAG.
Salary: £? - ? per year
Requirements
- Deep experience with Python
- Strong experience with AWS
- Hands‑on experience with LangChain
- Hands‑on experience with LangGraph
- Experience with Retrieval Augmented Generation (RAG)
- Experience with vector databases
- Experience with MLOps
- Experience with production machine learning platforms
- Experience with AI governance and engineering best practice
- Experience with PyTorch, TensorFlow, or Scikit‑learn
- Ability to design robust, scalable AI systems
- Ability to influence engineering standards across multiple product teams
Responsibilities
- Define engineering standards for enterprise AI
- Drive adoption of Agentic AI across multiple engineering teams
- Design production‑grade RAG architectures
- Establish LangGraph and LangChain implementation patterns
- Design scalable vector database retrieval strategies
- Lead best practice across MLOps, CI/CD, and model deployment
- Improve AI testing, evaluation, and observability
- Implement guardrails and hallucination mitigation
- Influence senior engineering stakeholders without direct line management
Technologies
- AI
- AWS
- CI/CD
- Machine Learning
- PyTorch
- Python
- TensorFlow
- Cloud
More
We are a global technology‑driven organisation scaling enterprise AI across our UK engineering function. We have already invested heavily in enterprise AI platforms and Agentic AI frameworks, and we are now focused on driving consistent adoption, establishing engineering standards, and enabling multiple engineering teams to build production‑ready AI solutions using common patterns and best practice. This is a Staff Engineer contract role based in London with three days per week on‑site, initially for six months with a long‑term programme roadmap, and it is inside IR35.
last updated 28 week of 2026
Staff ML Engineer employer: WeDoTech
Join a forward-thinking company that values innovation and collaboration, offering a dynamic work culture in Bristol. As a D365 F&O Solution Architect, you'll have the opportunity to lead impactful projects across Europe, with a strong focus on employee growth and development. Enjoy a competitive salary, flexible hybrid working arrangements, and the chance to shape the future of finance solutions in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Staff ML Engineer
✨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 WeDoTech.
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We think you need these skills to ace Staff ML Engineer
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!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at WeDoTech. 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 WeDoTech
✨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 WeDoTech!
✨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.
