Applied ML Engineer: Real-World Ops & Deployment

Platform Recruitment; Greater London; On-site; GBP 42,000 - 70,000; Full time

Job summary

Platform Recruitment in London is seeking a Machine Learning Engineer to design, build, and deploy advanced ML models that solve complex operational challenges in real-world environments. You will work with time-series data, forecasting, optimisation, and probabilistic modelling to create scalable systems in collaboration with engineering and product teams.

This hands-on role partners with a high-calibre founding team to move models from early validation to production deployment, handling

Qualifications

• Strong academic background in a quantitative STEM discipline such as Computer Science, Mathematics, Physics, Engineering, or related fields.
• Commercial experience developing machine learning solutions using Python and modern ML frameworks
• Strong understanding of applied machine learning techniques, particularly around modelling complex systems and large-scale datasets
• Experience working with time-series, forecasting, optimisation, or probabilistic modelling approaches
• Comfortable working with unstructured or inconsistent real-world data in production settings
• A problem-solving mindset with the ability to work autonomously within a fast-moving environment
• Interest in applying machine learning to operational, industrial, or physical systems

Responsibilities

• design, build, and deploy advanced machine learning models capable of solving complex operational challenges in real-world environments.
• Working closely with engineering and product teams, you will help develop scalable systems that can operate effectively with imperfect, high-volume data while contributing to the long-term technical direction of the platform.

Skills

Python

ML frameworks

Time-series

Forecasting

Optimization

Probabilistic modelling

Production data handling

Education

Quantitative STEM degree

Job description

Platform Recruitment in London is seeking a Machine Learning Engineer to design, build, and deploy advanced ML models that solve complex operational challenges in real-world environments. You will work with time-series data, forecasting, optimisation, and probabilistic modelling to create scalable systems in collaboration with engineering and product teams.

This hands-on role partners with a high-calibre founding team to move models from early validation to production deployment, handling