AI Research Scientist

Summary

Join Sword Health's AI Research team and contribute to building AI models that power a platform helping people live pain-free lives. You will participate in the entire development cycle of large deep learning models, collaborating with engineering and clinical teams to translate research into practical applications. The role involves preparing datasets, designing architectures, implementing solutions, training and evaluating models, and working towards ambitious research goals. You will also turn novel research ideas into working code and contribute to relevant research communities through publications. This position requires a PhD or enrollment in a PhD program in a relevant field, a publication record, proficiency in Python and machine learning frameworks, and the ability to design and analyze experiments. Sword Health offers a stimulating environment, career development, competitive salary, flexible hours, remote work options, health and well-being programs, and other benefits.

Requirements

• A PhD, or be currently enrolled in a PhD program and obtaining the degree prior to the start of employment, in Computer Science, Machine Learning, or a highly technical field
• A track record of research publications in peer-reviewed academic conferences or journals
• Proficiency in Python and experience with common machine learning frameworks (e.g., PyTorch, JAX, TensorFlow)
• Demonstrated ability to design experiments, and analyze and interpret their results
• Must have or be able to obtain work authorization in Portugal

Responsibilities

• Contribute to the entire development cycle of our cutting-edge large deep learning models
• Prepare datasets, design architectures, implement solutions, train and evaluate models to improve our products
• Collaborate across engineering and clinical teams to translate cutting-edge AI research into practical applications that have clinical implications
• Work towards long-term ambitious research goals based on developing novel solutions, while identifying immediate milestones
• Turning novel research ideas into working code
• Influence progress of relevant research communities by producing publications

Preferred Qualifications

• A strong research background and first-author publications in top-tier AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR, COLM, ACL, EMNLP)
• Deep expertise in one or more of the following areas: Large Language Models (LLMs), multimodal learning (vision, speech), deep learning, or reinforcement learning (RL)
• Alternatively , a proven track record of exceptional research contributions in another highly quantitative field (e.g., Physics, Applied Mathematics, Computational Statistics), coupled with a strong passion to apply your skills to AI for healthcare
• Industry experience taken during or after the PhD. e.g., Research Internships
• Experience taking research ideas from conception to implementation, including developing and debugging complex systems
• Strong communication skills and a history of effective collaboration on research projects
• A broader record of research excellence, demonstrated through grants, fellowships, patents, impactful open-source contributions, or relevant internships

Benefits

• A stimulating, fast-paced environment with lots of room for creativity
• A bright future at a promising high-tech startup company
• Career development and growth, with a competitive salary
• The opportunity to work with a talented team and to add real value to an innovative solution with the potential to change the future of healthcare
• A flexible environment where you can control your hours (remotely) with unlimited vacation
• Access to our health and well-being program (digital therapist sessions)
• Remote or Hybrid work policy: We have offices in Porto and Lisbon, so if you want to have face-to-face contact you can always work from there
• Health, dental and vision insurance
• Meal allowance
• Equity shares
• Remote work allowance
• Flexible working hours
• Work from home
• Discretionary vacation
• Snacks and beverages
• English class