Staff Machine Learning Engineer
Harnham
Manchester, United Kingdom
25 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Compensation
£ 100KJob location
Remote
Manchester, United Kingdom
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Big Data
Cloud Computing
Python
Machine Learning
TensorFlow
PyTorch
Spark
Deep Learning
Kafka
Machine Learning Operations
Job description
Looking for a role that gives you the opportunity to lead impactful machine learning projects while shaping the technical direction of a growing AI function? Excited by influencing strategy, mentoring engineers, and working fully remotely across Europe within a flexible, supportive environment?, As a Staff Machine Learning Engineer you will…
- Lead the design, development, and deployment of end-to-end ML solutions.
- Architect scalable ML systems and pipelines that integrate seamlessly with cloud infrastructure.
- Mentor engineers, championing best practices across coding, experimentation, and MLOps.
- Collaborate with Product and Engineering teams to define priorities and model strategy.
- Apply deep learning, NLP or classical ML techniques to real-world, high-impact problems.
- Uphold responsible AI principles across model development and evaluation.
Requirements
The successful Staff Machine Learning Engineer will have:
- Strong Python skills and experience with ML frameworks such as TensorFlow or PyTorch.
- Deep knowledge of machine learning and modern deep learning techniques.
- Experience deploying ML models to production using cloud platforms (AWS, GCP or Azure).
- Familiarity with big-data or distributed tools (Spark, Kafka or similar).
- A track record of leading complex ML projects and influencing technical decisions.
- Excellent communication skills across distributed, cross-functional teams.
About the company
This organisation is a forward-thinking technology business building data-driven products powered by advanced machine learning. They solve complex challenges across areas such as NLP, automation, and large-scale model deployment. With a distributed technical team across Europe, they emphasise collaboration, experimentation, and strong engineering standards. You'll join at a time of investment in AI, where your decisions directly shape the road-map and overall model capability.