About the role
Lead Machine Learning Engineer 12 Month FTC
Before applying for this role, please read the following information about this opportunity found below.
Remote UK, up to £90,000, 12 month fixed term contract
This is a rare opportunity to take ownership of machine learning delivery in a business that is actively investing in AI and moving from proof of concept into production. You will play a pivotal role in shaping how advanced ML and generative AI solutions are engineered, deployed and scaled, with genuine scope for the role to become permanent.
The Company
They are a large, well established UK organisation operating in a highly regulated, information rich environment. With thousands of colleagues nationwide, they combine deep domain expertise with a strong focus on people, quality and long term outcomes. Data and AI are now a strategic priority, with senior backing to build robust, production grade ML capability.
The Role
- Lead the engineering and productionisation of machine learning and generative AI solutions.
- Build and operate end to end ML pipelines, including data preparation, model deployment, monitoring and governance.
- Work closely with data scientists and data engineers to turn experiments and POCs into scalable, reliable services.
- Develop solutions for large scale unstructured data, including complex document processing and LLM ready data pipelines.
- Own MLOps practices, covering CI/CD, model serving, observability and lifecycle management.
- Provide hands on technical leadership, contributing to architecture decisions and best practice.
- Act as a delivery focused partner to stakeholders, confidently explaining trade offs and recommendations.
Your Skills & Experience
- Strong commercial experience as an ML Engineer or MLOps focused engineer, ideally with a software engineering background.
- Proven ability to deploy, operate and maintain machine learning systems in production.
- Hands on experience with cloud based data and ML platforms, particularly on Azure.
- Solid knowledge of Databricks and modern data engineering concepts such as lakehouse architectures.
- Experience preparing data and pipelines for LLM based use cases and NLP workloads.
- Strong Python skills, with experience building APIs or services, for example using FastAPI.
- Confidence working across the full delivery lifecycle, from design through to monitoring and optimisation.
- Clear communication skills and comfort working directly with non technical stakeholders.
What They Offer
- Excellent work life balance and a supportive, collaborative culture.
- The chance to shape ML engineering standards and capability from the ground up.
- Strong potential for the role to become permanent, with future people leadership opportunities. xwzovoh
How to Apply
If you are an experienced ML Engineer looking for a hands on role with real influence and long term potential, apply now to find out more.
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