Machine Learning Engineer
(Time Series & Predictive Modelling)
Build the future of AI-driven manufacturing
About the Role
We’re looking for a Machine Learning Engineer who thrives on solving complex, real-world problems using time series modelling, statistics, and deep learning.
In this role, you’ll design and optimise advanced predictive models that power next-generation manufacturing systems. You’ll focus purely on model development and performance not pipelines working alongside a dedicated engineering team that handles data infrastructure.
You’ll also collaborate with machine vision engineers to create multi-modal AI systems, combining sensor data with visual intelligence.
What You’ll Do
* Develop high-performance models for:
o Time series forecasting
o Anomaly detection
o System optimisation
* Apply statistical and probabilistic methods to understand system behaviour and variability
* Build deep learning models for sequential data (e.g. LSTM, GRU, Transformers)
* Turn complex industrial datasets into actionable insights
* Collaborate with data engineers to ensure clean, production-ready inputs
* Work with vision ML engineers to create integrated, multi-modal models
* Evaluate and tune models using rigorous experimentation
* Support deployment by packaging models for production integration
* Monitor performance and drive continuous improvement
What You Bring
* Degree in Computer Science, Engineering, Mathematics, Statistics, or similar
* Strong experience in time series modelling and analysis
* Solid foundation in statistics and probabilistic modelling
* Hands-on experience with neural networks for sequential data
* Proficiency in Python and ML frameworks (PyTorch, TensorFlow)
* Experience working with messy, real-world data (noise, gaps, irregular sampling)
* Ability to translate complex data into robust, production-ready models
* Strong collaboration skills across technical teams
Nice to Have
* Exposure to computer vision / machine vision
* Experience working alongside (not owning) data engineering pipelines
* Familiarity with multi-modal learning (sensor + vision data)
* Background in manufacturing, robotics, or industrial systems
* Understanding of MLOps and deployment patterns
What Success Looks Like
* Models that deliver measurable improvements in prediction accuracy and system performance
* Seamless collaboration across ML, vision, and engineering teams
* Solutions that are robust, scalable, and production-ready
Why Join Us
* Work on cutting-edge AI in advanced manufacturing
* Be part of a highly collaborative, cross-functional team
* Competitive salary + strong growth opportunities
* Flexible working arrangements