Machine Learning Engineer (BE) at CluePoints

, , Belgium -

Full Time

Start Date

Immediate

Expiry Date

25 Jun, 26

Salary

0.0

Posted On

27 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, Python, TensorFlow, PyTorch, Git, Deep Learning, Natural Language Processing, GPU Computing, Statistics, Artificial Intelligence

Industry

Software Development

Description

At CluePoints, we’re redefining how clinical trials are run. As the premier provider of Risk-Based Quality Management (RBQM) and Data Quality Oversight software, we harness advanced statistics, artificial intelligence, and machine learning to ensure the quality, accuracy, and integrity of clinical trial data, helping life sciences organizations bring safer, more effective treatments to patients faster. We’re proud to be an ambitious, fast-growing technology scale-up with a dynamic and diverse international team representing more than 40 nationalities. Collaboration, flexibility, and continuous learning are part of our DNA. At CluePoints, you’ll find a culture where you can grow, make an impact, and have fun along the way. Guided by our values of Care, Passion, and Smart Disruption, we’re united by a shared mission: to create smarter ways to run efficient clinical trials and deliver AI-powered insights that improve human outcomes worldwide. We’re looking for a Machine Learning Engineer to join our team and contribute to our mission of transforming clinical research through data-driven insights. Main Qualifications * Master or PhD in Computer sciences or quantitative fields (maths, physics, ...) * Professional experience in machine learning / data science * Efficient in Python * Good knowledge in at least one deep learning platform like TensorFlow or PyTorch * Experience with code versioning tools such as Git Preferred Qualifications: * Experience with deep learning and natural language Processing * Experience in supporting deployments of machine learning models * Experience with medical data * Experience in GPU computing As a member of our Research team: * You develop new machine learning models to enhance the CluePoints web platform and/or to develop new products. * You identify promising ML techniques from scientific literature and assess their viability * You leverage relevant open-source resources and keep yourself up-to-date to new developments in this area * You produce robust and clean python code * You follow ML best practices to keep track of experiments and models * You identify new fields of applications for machine learning and deep learning within CluePoints and contribute to increased adoption of machine learning within the healthcare industry * You stay on the edge of relevant research and help CluePoints to continue increasing its scientific visibility by participating at scientific conferences and publishing in scientific journals 🇧🇪 What We Offer – Belgium · Health Insurance through Alan (100% hospitalisation cover, 80% ambulatory and dental) · Mobility Budget for eco-transport, housing, or car allowance (flexible 3-pillar system) · Group Insurance Plan with 6–12% employer pension contribution based on seniority · Meal Vouchers (€8/day) and Eco Vouchers for sustainable purchases · A hub-based hybrid model that blends flexibility with purpose — connecting teams through collaboration, learning, and a vibrant social culture. Equal Opportunities & GDPR Notice CluePoints is an equal opportunities employer. We value and respect diversity in our workforce and do not tolerate discrimination based on gender, age, disability, ethnic origin, religion, sexual orientation, or any other protected ground under Belgian law. Personal data collected as part of your application will be processed in compliance with the EU GDPR and Belgian data protection legislation. You have the right to access, correct, or delete your personal data at any time by contacting privacy@cluepoints.com.

Responsibilities

The engineer will develop new machine learning models to enhance the web platform and develop new products by identifying promising ML techniques from scientific literature. They will also produce robust Python code, follow ML best practices, and contribute to increased adoption of machine learning within the healthcare industry.