Machine Learning Engineer Offline

About the Role:
We are looking for a skilled and experienced Machine Learning Engineer to join our team in the healthcare domain, with a specific focus on orthodontics. You will play a key role in developing and implementing ML-driven solutions to support diagnosis, treatment planning, and predictive analytics in dental and orthodontic care. Your work will directly contribute to improving patient outcomes and enhancing clinical workflows.

Responsibilities:

• Design, develop, and deploy ML models tailored for orthodontic applications (e.g., image analysis, anomaly detection, treatment prediction).
• Collaborate closely with data scientists, dental professionals, and software engineers to define and refine project goals.
• Preprocess and analyze large datasets, including 2D/3D medical images, patient records, and treatment histories.
• Ensure high model performance, robustness, and clinical interpretability.
• Conduct research and stay updated on the latest ML/AI trends in the healthcare and dental domains.
• Document and present technical solutions and findings to both technical and non-technical stakeholders.

Requirements:

• 4+ years of hands-on experience in machine learning, preferably in the healthcare domain.
• Strong knowledge of ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Solid experience working with medical imaging (X-rays, CBCT, intraoral scans) is a major plus.
• Proficiency in Python and common data science libraries.
• Experience with data preprocessing, annotation pipelines, and model evaluation.
• Familiarity with regulatory and privacy standards (e.g., HIPAA, GDPR) is an advantage.
• Excellent problem-solving skills and attention to detail.
• English level: Upper-Intermediate or higher – ability to participate in technical discussions and write clear documentation.

Nice to Have:

• Experience with 3D data processing and computer vision techniques.
• Background in dental or orthodontic workflows and terminology.
• Publications or contributions in relevant ML/AI or medical imaging conferences.