Full Time Computing and Machine Learning Intern Jobs, in PreciX - Maukerja

Company Description PreciX designs kinematic knee health screening products that support more precise diagnosis and recovery inside and outside clinical settings. The company’s flagship product, GATOR, delivers accuracy, speed, and accessibility for musculoskeletal assessment. GATOR analyzes true bone biomechanical measurements from dynamic movement to generate actionable insights that inform diagnosis and treatment. PreciX focuses on combining advanced computation with practical healthcare applications to improve patient outcomes. For more information, connect with the team on LinkedIn and visit *************

Role Description

1. Design, train, and evaluate machine learning models to detect biomechanical markers of ACL injury and monitor recovery trajectories
2. Preprocess and analyse time-series data collected from multi-sensor wearable devices, ensuring high data fidelity
3. Develop, test, and deploy end-to-end ML pipelines, from model training to real-time inference
4. Co-develop a Progressive Web App (PWA) for displaying diagnostic outputs and patient insights, optimised for clinician usability
5. Contribute to backend API development (e.g. Flask, FastAPI, or Node.js) to support frontend-ML integration
6. Work with embedded team to validate model performance and ensure compatibility with device firmware and data protocols
7. Assist in documenting ML workflows and software systems for compliance with medical device regulatory requirements
8. Collaborate with multidisciplinary teams from ASTAR, DxDHub, and clinical partners to align system outputs with real-world clinical workflows

Qualifications

• Foundational knowledge in Computer Science and Algorithms, with the ability to write clean, efficient, and well-documented code.
• Strong understanding of Machine Learning and Deep Learning concepts, including model training, evaluation, and optimization.
• Proficiency in Statistics for data analysis, hypothesis testing, and interpretation of experimental results is an advantage.
• Experience with relevant programming languages and tools (such as Python, TensorFlow or PyTorch, NumPy, and data visualization libraries).
• Currently pursuing or having completed a degree in Computer Science, Data Science, Engineering, or a related quantitative field.
• Ability to work collaboratively in an interdisciplinary environment and communicate technical findings clearly to non-technical stakeholders.
• Interest in healthcare technology, biomechanics, or medical devices is an advantage.