Company description

Are you a builder of intelligence who thrives at the intersection of data, experimentation, and innovation — where algorithms evolve into real-world impact?

We’re partnering with a global technology leader pushing the boundaries of applied AI - from predictive analytics and automation to intelligent decision systems that redefine how businesses operate.

Searching for a Machine Learning Engineer who combines engineering precision with scientific curiosity - someone who can architect models that don’t just work, but learn, adapt, and create value at scale.

Your Role 

You’ll be the engine behind intelligent systems - designing, building, and deploying ML pipelines that turn raw data into real outcomes. Working alongside top-tier data scientists, engineers, and domain experts, you’ll bring models from concept to production with speed, rigour, and creativity.

What You’ll Do:

Develop, train, and deploy machine learning models at scale using Python, TensorFlow, and PyTorch.

Collaborate with data engineers to ensure robust feature pipelines and clean, reliable datasets.

Key Responsibilities

- Develop, train, and deploy machine learning models at scale using Python, TensorFlow, and PyTorch.

- Collaborate with data engineers to ensure robust feature pipelines and clean, reliable datasets.

- Optimise model performance, interpretability, and fairness across diverse applications.

- Implement CI/CD for ML models, integrating with modern MLOps frameworks.

- Continuously monitor models in production, retraining and improving accuracy over time.

Required Skills & Experience

Proven experience building and deploying machine learning models in production environments.
Strong skills in Python, ML frameworks (TensorFlow/PyTorch), and data processing (Pandas, Spark).
Understanding of software engineering best practices - testing, versioning, and CI/CD.