We are seeking an exceptional Senior AI & Data Science Engineer to join our core team and lead the development of next-generation AI systems in healthcare. This full-time, long-term role (conditioned on project funding) is ideal for someone eager to work at the intersection of AI, data science, and healthcare, solving complex real-world challenges — from data processing and model development to clinical integration and personalized treatment.

• Design, develop, and deploy advanced AI and machine learning models to process, analyze, and interpret medical and clinical data (structured, unstructured, text, and imaging).
• Build end-to-end data and AI pipelines — from ingestion and preprocessing to experimentation, deployment, and continuous optimization — with a strong focus on scalability and automation.
• Develop and integrate multi-model AI systems and intelligent agents capable of supporting complex decision-making, workflow automation, and adaptive personalization in healthcare.
• Contribute to the development of systems supporting personalized treatment pathways, including modeling patient response to therapies and supporting individualized care plans.
• Lead or contribute to the experimentation, evaluation, and validation of models in clinical or near-clinical settings.
• Work collaboratively with clinicians, researchers, and engineers to translate AI research into deployable, real-world solutions.
• Ensure compliance with data governance, healthcare standards (GDPR, HIPAA, etc.), and ethical AI principles in all solutions.
  

• 7+ years of experience in AI, machine learning, or data science, ideally with a focus on healthcare or life sciences.
• Deep expertise in data science and AI workflows, including exploratory analysis, feature engineering, model training, optimization, and validation.
• Proven experience building production-ready, scalable AI systems and integrating them into real-world workflows.
• Strong experience with ETL pipelines, data engineering, and data warehousing for large, complex medical datasets.
• Advanced understanding of machine learning, deep learning, statistics, computer vision, and unsupervised learning, with hands-on experience applying them to healthcare use cases.
• Practical experience with generative AI, transformers, variational autoencoders (VAEs), LLMs, and fusion models, as well as building and deploying AI agents.
• Strong programming skills in Python (preferred) or R, with experience using TensorFlow, PyTorch, or similar frameworks.
• Proven ability to handle multimodal healthcare data (e.g., imaging, tabular, textual) and design solutions across diverse data types.
• Deep understanding of data governance, privacy regulations, and compliance frameworks relevant to healthcare.
• Excellent communication skills and the ability to work cross-functionally with clinical, technical, and business stakeholders.
• Strong problem-solving skills, adaptability, and a collaborative mindset with a focus on performance and results.
  

• Master’s degree in Data Science, Computer Science, AI, Biomedical Engineering, Mathematics, Statistics, or a closely related field.
• Experience in clinical AI research, digital health solutions, or healthcare product development is a strong advantage.
• Familiarity with cloud infrastructure (AWS, GCP, Azure) and scalable ML deployment practices.