Senior Machine Learning Applied Scientist

Master’s or PhD degree in Computer Science, Statistics, Mathematics, Physics, or a related field
5+ years of industry experience in machine learning or related field
Strong background in machine learning, deep learning, and computer vision
Experience with unsupervised learning techniques such as autoencoders, generative models, and contrastive learning
Experience with label noise mitigation techniques, such as co-teaching or mentor-guided learning
Familiarity with transformer-based architectures such as BERT or GPT
Experience with diffusion denoising techniques
Strong programming skills in Python and proficiency with popular machine learning libraries such as PyTorch or TensorFlow
Strong communication and teamwork skills

Design, implement, and evaluate machine learning models for a variety of applications, with a focus on addressing challenges related to label noise, unsupervised learning, and diffusion denoising
Collaborate with other members of our AI team, as well as with radiologists, product managers, and support engineers, to build end-to-end analytics solutions that deliver actionable insights to our customers
Stay up-to-date with the latest advances in machine learning and data science, and apply these techniques to our work as appropriate
Participate in code reviews and help ensure that code quality and best practices are maintained across the team
Work with cross-functional teams to ensure that our data science solutions are well integrated with other products and services

Familiarity with cloud computing platforms such as AWS or Google Cloud
Experience with medical imaging and/or healthcare data
Strong publication record in top-tier machine learning or computer vision conferences/journals