Barrington James

Machine Learning Engineer

Job description

New contract opportunity in London for a Machine Learning Engineer on a 6 month contract to work remotely to implement and optimize machine learning algorithms that extract meaningful insights.

About The Company

The company is a cutting-edge technology company that specializes in developing innovative healthcare solutions dedicated to revolutionizing the way individuals monitor their cardiovascular health.

Using their state-of-the-art smartphone application that provides access to ECG and PPG signals. Their mission is to empower people with the tools they need to proactively manage their heart health and improve their overall well-being.

Job Overview

We are seeking a highly motivated and skilled Machine Learning Engineer to join our dynamic team. As a Machine Learning Engineer, you will play a pivotal role in the development of our smartphone application that enables users to access and interpret ECG and PPG signals for personalized heart health insights.

You will work closely with cross-functional teams to design, implement, and optimize machine learning algorithms that extract meaningful insights from raw sensor data and contribute to the enhancement of our user-friendly interface.


  • Work alongside product managers, software engineers, and domain experts to understand requirements and translate them into effective machine learning solutions.
  • Design and implement robust machine learning models for processing ECG and PPG signals, feature extraction, anomaly detection, and health parameter estimation.
  • Pre-process, clean, and curate large datasets of ECG and PPG signals to ensure high data quality and integrity.
  • Apply advanced signal processing techniques and machine learning algorithms to extract relevant information from raw sensor data.
  • Optimize and fine-tune machine learning models for real-time performance on mobile devices while considering computational efficiency and battery consumption.
  • Conduct experiments, perform data analysis, and iterate on models to improve accuracy, sensitivity, and specificity of heart health insights.
  • Collaborate with the software development team to integrate machine learning models into the smartphone application.
  • Stay up to date with the latest advancements in machine learning, signal processing, and mobile technologies relevant to heart health monitoring.

Education/ Qualifications

  • Master's or Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field with a focus on machine learning and signal processing.

Required Skills & Experience

  • Strong understanding of signal processing techniques, feature extraction, and time-domain and frequency-domain analysis.
  • Familiarity with mobile development and optimization for Android and iOS platforms is a plus.
  • Excellent problem-solving skills and ability to work independently and collaboratively in a fast-paced, interdisciplinary environment.
  • Strong communication skills to effectively convey complex technical concepts to both technical and non-technical team members.
  • Experience with cloud computing platforms and tools for data storage and processing is desirable.
  • Publications or contributions to relevant conferences/journals or open-source projects is a plus.
  • Proven experience in developing and implementing machine learning models for signal processing, time series analysis, or biomedical applications.
  • Proficiency in programming languages such as Python and experience with machine learning libraries (e.g., TensorFlow, PyTorch).

If you interested in the opportunity and would like to find out more apply or reach out to Luke Ottley ( for a follow up to discuss in further detail.

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