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- Tasks: Design and deploy cutting-edge machine learning and Generative AI solutions.
- Company: Join a leading global organisation in the Data & Analytics field.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Why this job: Make a real impact by turning innovative models into production-ready systems.
- Qualifications: Strong Python skills and experience with ML frameworks like TensorFlow and PyTorch.
- Other info: Dynamic role with exposure to enterprise-scale AI initiatives and excellent career advancement.
The predicted salary is between 60000 - 84000 ÂŁ per year.
We are partnering with a leading global organisation to recruit an experienced Machine Learning Engineer to join a highly regarded Data & Analytics function. This role offers the opportunity to work on enterprise‑scale AI and Generative AI initiatives, building production‑grade solutions that drive automation, prediction, and decision‑making across the business.
This is an excellent opportunity for someone who enjoys taking models from experimentation through to real‑world deployment, while working closely with data scientists, engineers, and senior stakeholders.
As a Machine Learning Engineer, you will play a key role in designing, building, and deploying scalable machine learning and GenAI solutions. You’ll work on complex, multi‑layered datasets and contribute to model governance, evaluation, and optimisation in regulated, real‑world environments. You will also be involved in reviewing and assessing GenAI use cases from across the business and supporting robust governance and risk controls around model usage.
Key Responsibilities:- Design, build, and productionise machine learning and Generative AI solutions that meet enterprise standards for scalability, reliability, and performance.
- Partner closely with data scientists to turn experimental models into well‑engineered, production‑ready systems.
- Develop and maintain end‑to‑end ML pipelines, including feature engineering, training, evaluation, versioning, monitoring, and automated retraining.
- Contribute to MLOps capabilities, including CI/CD pipelines, model registries, infrastructure automation, and containerised deployments.
- Perform robust model evaluation, including benchmarking, drift detection, fairness analysis, and performance optimisation.
- Collaborate with data engineers and architects to enhance data quality, data flows, and platform capabilities.
- Lead experimentation using modern ML frameworks to assess new algorithms and technologies and make recommendations on adoption.
- Support model governance processes, ensuring compliance with internal standards, documentation, transparency, and regulatory requirements.
- Advise business and product teams on opportunities for automation, predictive modelling, and GenAI enablement.
- Contribute to reusable ML components, internal frameworks, and engineering best practices.
- Stay up to date with emerging AI trends, tooling, and foundation models to inform strategic decision‑making.
You will be a strong hands‑on Machine Learning Engineer with solid analytical foundations and experience deploying models into production environments.
Key skills and experience include:- Strong programming skills in Python.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit‑learn.
- Advanced knowledge of statistics, probability, and optimisation techniques.
- Proven experience building, testing, tuning, and optimising machine learning models.
- Comfortable working with large, complex datasets; experience with SQL and data preprocessing.
- Experience or strong exposure to MLOps, including CI/CD, Docker, Kubernetes, and cloud platforms (AWS preferred).
- Understanding of Generative AI use cases and model governance or compliance processes.
Machine Learning Engineer in Manchester employer: Robert Walters UK
Contact Detail:
Robert Walters UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with other Machine Learning Engineers. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and Generative AI. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and approach real-world problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Machine Learning Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with Python, machine learning frameworks, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include specific examples of projects where you've taken models from experimentation to deployment. This will help us understand your hands-on experience and how you tackle real-world challenges in ML and GenAI.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for key achievements and avoid jargon unless it's necessary. We appreciate straightforward communication that gets to the heart of your experience.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you're keen on joining our team at StudySmarter!
How to prepare for a job interview at Robert Walters UK
✨Know Your Tech Stack
Make sure you’re well-versed in the programming languages and frameworks mentioned in the job description, especially Python, TensorFlow, and PyTorch. Brush up on your MLOps knowledge too, as they'll likely ask about CI/CD processes and cloud platforms like AWS.
✨Showcase Your Projects
Prepare to discuss specific projects where you've taken machine learning models from experimentation to deployment. Highlight your role in building end-to-end ML pipelines and any challenges you faced, along with how you overcame them.
✨Understand Generative AI
Since this role involves Generative AI, be ready to discuss its use cases and implications. Familiarise yourself with recent trends and advancements in the field, and think about how they could apply to the organisation’s needs.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the company’s data governance and model evaluation processes. This not only demonstrates your knowledge but also your enthusiasm for contributing to their projects and initiatives.
