Machine Learning Engineer

Location London
Discipline: Machine Learning
Contact name: Eddie Woodley

Contact email:
Published: 15 days ago

We are hiring for a company utilizing behavioral data to develop Personal Healthcare Agents by combining sensor-based technologies with natural language processing. Their team consists of committed digital health researchers, machine learning experts, and clinicians from leading institutions in academia and industry.

What you will be doing

  • Creating and maintaining a platform for ongoing patient engagement.

  • Crafting methods to efficiently gather and merge data from various sensors found in smartphones and wearables.

  • Implementing feature engineering techniques to derive valuable insights from sensor data.

  • Designing and deploying robust models for activity recognition to categorize and interpret human activities based on sensor data.

  • Tackling challenges related to missing data and variations in sampled data.

  • Communicating progress and updates to leadership and team members.

  • Collaborating with colleagues to achieve shared objectives.

  • Presenting research findings clearly, both verbally and in writing.

What the company is looking for

  • A degree in Computer Science, Software Engineering, Statistics, Data Science, or a related field.

  • Over 5 years of industry experience in relevant positions.

  • Strong expertise in machine learning, statistics, and experience in areas like time-series modeling, deep learning, and self-supervised learning.

  • Hands-on experience with data from smartphone and wearable sensors, along with implementing activity recognition algorithms.

  • Proven track record in software engineering, particularly in developing, maintaining, and deploying ML-based applications.

  • Proficiency in programming languages like Python, data processing tools such as Pandas and Seaborn, and ML frameworks like Tensorflow and PyTorch.

  • A keen interest in constructing secure and dependable AI tools for practical applications.

Desirable qualifications

  • Collaborated with researchers in an interdisciplinary environment.

  • Worked with real-world datasets featuring serial dependencies.

  • Previous experience in a healthcare environment.