Medeloop seeks a Machine Learning Engineer with a deep theoretical foundation in machine learning and artificial intelligence to develop the next-generation AI solutions in healthcare & clinical research. The ideal candidate combines years of hands-on industry experience with a strong academic foundation and a track record of leading impactful AI initiatives. You will design and deploy state-of-the-art machine learning models, agentic workflows, and data pipelines, while collaborating with multidisciplinary teams to influence Medeloop’s technological direction.

Key Responsibilities:

• Drive the development of cutting-edge machine learning models and frameworks to address complex challenges in healthcare data.
• Partner with the Head of Engineering and other leaders to shape Medeloop’s AI strategy.
• Architect, train, and deploy machine learning models for large-scale, high-impact healthcare datasets.
• Engage with researchers and healthcare professionals to understand their challenges and deliver tailored solutions.
• Stay at the forefront of machine learning advancements, contributing to the company’s position as a leader in AI for healthcare.

Who You Are:

• A strong understanding of traditional & theoretical machine learning (emphasis in NLP and reinforcement learning), mathematical modeling, and statistical methods.
• Experience working with vector databases and semantic search engines.
• 2+ years of experience in machine learning engineering, with a proven ability to bridge theoretical insights and industry applications.
• Expertise in popular machine learning frameworks such as PyTorch, Hugging Face, SageMaker, Weights & Biases, etc.
• Experience with both training and evaluating ML models.
• Proficiency in AWS infra, CDK, and experience with distributed learning.
• Ability to bridge data engineering and machine learning engineering.
• An out-of-the-box thinker who embraces unsolved challenges.
• Ability to work in a fast-paced environment and play multiple roles.

Bonus: A strong publication record in leading AI or machine learning conferences/journals is highly desirable.