Open roleExternal
Machine Learning Engineer
- cambridge, cambridgeshire, CB1, United Kingdom
- Remote
- Full time
- £72,000 - £72,000 Per Annum
Job Description
About the Role
Our client is seeking an innovative and results-oriented Machine Learning Engineer to join their cutting-edge research and development team in Cambridge . This role involves designing, building, and deploying machine learning models and systems that drive intelligent solutions for their products and services. You will collaborate with data scientists, software engineers, and product teams to bring advanced AI capabilities to life. This is an exceptional opportunity for a talented individual passionate about ML to work on challenging problems and contribute to groundbreaking advancements in a leading tech hub.
Key Responsibilities
- Develop, train, and evaluate machine learning models using Python and relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Build and maintain scalable ML pipelines for data processing, feature engineering, and model deployment.
- Collaborate with data scientists to productionize ML models and integrate them into existing software systems.
- Design and implement strategies for model monitoring, performance tracking, and retraining.
- Stay abreast of the latest research and advancements in machine learning and artificial intelligence.
- Work with large datasets and optimize algorithms for efficiency and performance.
Requirements
- Master's or PhD in Computer Science, Machine Learning, AI, Statistics, or a related quantitative field.
- Proven experience as a Machine Learning Engineer or in a similar role involving ML model development and deployment.
- Strong programming skills in Python and extensive experience with ML frameworks.
- Solid understanding of algorithms, data structures, and statistical modeling.
- Experience with cloud platforms (AWS, Azure, GCP) and their ML services.
- Familiarity with MLOps practices and tools for model deployment and lifecycle management.
Benefits
- Highly competitive salary and generous performance-based bonuses.
- Flexible remote working arrangements to support work-life balance.
- Comprehensive private health, dental, and vision insurance.
- Contributory pension scheme and life assurance.
- Significant budget for continuous learning, conferences, and certifications.
- Access to state-of-the-art research facilities and a stimulating work environment in Cambridge .