About the Role
Are you a strong Machine Learning Engineer who wants to see your models running in production, not sitting in a notebook?
Predictiva is looking for a Machine Learning Engineer to join our Edinburgh team. You will work across our autonomous trading platforms and applied AI projects, building, deploying, and iterating on production-grade ML systems alongside a team of engineers, researchers, and financial experts.
This is a hands-on engineering role. You will be expected to own work end-to-end, from data preparation and model development through to deployment and monitoring in live environments.
About Predictiva
Predictiva is an award-winning AI FinTech company developing autonomous trading systems that leverage advanced machine learning to trade global financial markets. Our mission is to make cutting-edge AI trading technology accessible to professionals and institutions worldwide.
Our platforms serve both enterprise clients and a growing retail user base across multiple countries. We also partner with financial institutions across the UK, Europe, and the GCC to deliver applied AI implementations in production environments. Backed by a team of researchers, engineers, and financial experts, Predictiva is recognised as one of the Top 50 Data-Driven AI Startups in Europe and is a winner of the Innovate UK Smart Grant.
Key Responsibilities
As a Machine Learning Engineer at Predictiva, you will:
- Design, develop, and train machine learning models for deployment in production financial systems.
- Own the full model lifecycle from data preparation and experimentation through to deployment, monitoring, and iteration.
- Build and maintain robust ML pipelines, including experiment tracking, model evaluation, and performance monitoring.
- Work with complex financial time-series data, including preparation, processing, and feature engineering.
- Collaborate closely with software engineers and DevOps to ensure reliable and efficient model deployment.
- Translate research findings and ideas into production-ready systems.
- Present findings and model behaviour clearly to both technical and non-technical stakeholders.
About You
We are looking for someone who has built and shipped ML systems in production, not just experimented in isolation. You should be comfortable owning your work independently and moving at pace in a fast-moving engineering environment.
Essential qualifications:
- MSc in Artificial Intelligence, Machine Learning, Computer Science, or a related field.
- Strong Python programming skills and software engineering fundamentals.
- Solid understanding of machine learning algorithms, model architectures, and evaluation techniques.
- Experience using deep learning frameworks such as PyTorch or TensorFlow.
- Experience handling complex datasets and time-series data.
- Experience deploying ML models into production environments.
- Ability to work independently, manage your own workload, and communicate progress clearly.
Desirable qualifications:
- PhD in Artificial Intelligence, Machine Learning, Computer Science, or a related field.
- Experience with Reinforcement Learning algorithms and sequential decision-making problems.
- Experience with experiment tracking and model lifecycle tools such as Weights and Biases or MLflow.
- Experience with cloud platforms (AWS, Azure, GCP) and containerised deployments.
- Interest or prior experience in financial markets or fintech.
What We Offer
- Competitive salary.
- Pension scheme.
- Employee share options through our equity pool.
- 28 days paid annual leave plus UK bank holidays.
- Free unlimited personal access to our trading platforms.
- Access to powerful cloud-based and on-premises compute infrastructure.
- Company laptop and technical tools.
- The opportunity to work on production ML systems deployed in live financial markets.
- A collaborative environment of scientists, engineers, and financial innovators.
Why Join Us
At Predictiva, machine learning is not a side feature. It is the product. You will work in an environment where research and engineering are taken equally seriously, on systems that are live, measurable, and impactful. If you want to build ML systems that actually ship and want to grow quickly in a technically ambitious team, this is the right place.
