Machine Learning Engineer

5 days ago

London, Greater London, United Kingdom Machine Medicine Technologies Full time
About Us

Machine Medicine Technologies (MMT) is a pioneering company that leverages computer vision and computational statistics to revolutionize neurological assessments. Our flagship product, KELVIN, enables motor assessments in Parkinson's disease to be performed, recorded, and utilized more efficiently than ever before. KELVIN PD is already in use at clinical sites across several countries, and we aim to develop the platform into a comprehensive tool for patient selection, surgical planning, and device programming for machine brain interfacing.

Job Summary

We are seeking an ambitious and capable Machine Learning Engineer to join our team. As a key member of our engineering team, you will be responsible for designing and developing ML pipelines, deploying machine learning models as microservices into production, and contributing to our research and academic papers.

Key Responsibilities
  • Design and Development: Lead the design and development of ML pipelines, ensuring they are scalable, efficient, and meet the required quality standards.
  • Model Deployment: Deploy machine learning models as microservices into production, ensuring seamless integration with our existing infrastructure.
  • Research and Development: Contribute to our research and academic papers, staying up-to-date with the latest advancements in machine learning and computer vision.
Requirements
  • Commercial Python Experience: Minimum 2 years of experience in commercial Python development.
  • Machine Learning Experience: Demonstrable experience deploying and monitoring machine learning models.
  • ML Techniques and Statistical Concepts: Strong understanding of machine learning techniques and statistical concepts.
  • Education: BSc or MSc in a relevant quantitative subject (computer science, mathematical engineering, etc.).
  • Deep Learning Frameworks: Experience with at least one deep learning framework (PyTorch or TensorFlow).
  • Configuration Management: Experience with configuration management (Docker, Kubernetes).
  • Cloud Infrastructure: Familiarity with cloud infrastructure (AWS, EC2, S3, Batch).
Desirable Skills
  • Communication and Time Management: Good communication and time management skills.
  • Biomedical Sector Experience: Previous experience in the biomedical sector.
Company Benefits
  • Competitive Salary: Competitive salary package.
  • Employee Equity Programme: Employee equity programme.
  • Pension: Pension scheme.
  • Annual Leave: 25 days annual leave (including bank holidays).

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