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Senior Machine Learning Engineer
2 months ago
We are seeking a highly skilled Senior Machine Learning Engineer to join our client's team in Buckinghamshire, UK. The successful candidate will develop and implement advanced computer vision models and manage large datasets, ensuring data quality and integrity.
Key Responsibilities- Computer Vision Model Development: Design, develop, and train advanced computer vision models using machine learning frameworks such as PyTorch.
- Data Management: Manage and process large datasets, maintaining data quality and integrity.
- Pipeline Design: Design and implement robust CI/CD pipelines for machine learning models.
- Performance Optimization: Optimize model performance using CUDA.
- Deployment: Deploy machine learning models into production environments, ensuring scalability and reliability.
- Collaboration: Work with cross-functional teams to integrate machine learning capabilities into products.
- Technical Leadership: Provide technical leadership and mentorship to a small team of engineers and data scientists.
- Continuous Learning: Stay updated with the latest developments in machine learning and computer vision.
- Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Technical Expertise: 3+ years' industry experience in developing and training computer vision models.
- Programming Skills: Strong programming skills in Python and experience with machine learning frameworks such as PyTorch.
- Data Handling: Experience in managing and processing large datasets.
- Pipeline Knowledge: Familiarity with CI/CD pipelines for machine learning models.
- Performance Tools: Proficiency in using performance optimization tools like CUDA.
- Production Deployment: Experience in deploying machine learning models in production environments.
- Leadership: Experience in leading and mentoring engineering teams.
- Competitive Salary: Circa £45-70,000 DOE
- Additional Benefits: Car salary sacrifice scheme, cycle to work scheme, statutory pension, and share options.
- Work-Life Balance: Hybrid working model with flexibility.
- Career Growth: Opportunities for professional development and growth in a dynamic environment.
