Machine Learning Research Engineer, Health AI

As a research-focused Software Engineer at Google, your role involves setting up large-scale tests and deploying innovative ideas quickly. You will have the opportunity to work on real-world problems such as artificial intelligence, data mining, natural language processing, and more. Your responsibilities include collaborating with research programs at universities, conducting experiments, prototyping implementations, and designing new architectures. Key Responsibilities: - Innovate, implement, and evaluate machine learning algorithms over multimodal healthcare data. - Author publications of novel research in leading scientific journals and conferences. - Design, implement, and deliver complex pieces of research and infrastructure as part of a multi-disciplinary team. - Manipulate and evaluate large and complex medical datasets. - Work with internal and external stakeholders, including Product Managers, Clinicians, UX researchers, and Regulatory Advisors. Qualifications Required: - Bachelor's degree or equivalent practical experience. - 2 years of experience with software engineering in one or more programming languages, or 1 year of experience with an advanced degree. - 2 years of experience with data structures or algorithms. - Machine learning experience. - One or more research publication submissions for conferences, journals, or public repositories. Preferred Qualifications: - Experience with fine-tuning and evaluating generative AI models. - Experience conducting Deep Learning experiments. - Experience with machine learning in the health domain. - Working knowledge of JAX, TensorFlow, or PyTorch. - Interest in the application of research to healthcare. At Health AI, the mission is to catalyse the adoption of human-centered AI in healthcare and medicine. The team conducts machine learning research to advance foundational ML capabilities and build agents that enable breakthrough capabilities in collaboration with other teams in consumer health and adjacent domains such as education. You will be actively contributing to the wider research community by partnering with universities and publishing papers. As a research-focused Software Engineer at Google, your role involves setting up large-scale tests and deploying innovative ideas quickly. You will have the opportunity to work on real-world problems such as artificial intelligence, data mining, natural language processing, and more. Your responsibilities include collaborating with research programs at universities, conducting experiments, prototyping implementations, and designing new architectures. Key Responsibilities: - Innovate, implement, and evaluate machine learning algorithms over multimodal healthcare data. - Author publications of novel research in leading scientific journals and conferences. - Design, implement, and deliver complex pieces of research and infrastructure as part of a multi-disciplinary team. - Manipulate and evaluate large and complex medical datasets. - Work with internal and external stakeholders, including Product Managers, Clinicians, UX researchers, and Regulatory Advisors. Qualifications Required: - Bachelor's degree or equivalent practical experience. - 2 years of experience with software engineering in one or more programming languages, or 1 year of experience with an advanced degree. - 2 years of experience with data structures or algorithms. - Machine learning experience. - One or more research publication submissions for conferences, journals, or public repositories. Preferred Qualifications: - Experience with fine-tuning and evaluating generative AI models. - Experience conducting Deep Learning experiments. - Experience with machine learning in the health domain. - Working knowledge of JAX, TensorFlow, or PyTorch. - Interest in the application of research to healthcare. At Health AI, the mission is to catalyse the adoption of human-centered AI in healthcare and medicine. The team conducts machine learning research to advance foundational ML capabilities and build agents that enable breakthrough capabilities in collaboration with other teams in consumer health and adjacent domains such as education. You will be actively contributing to the wider research community by partnering with universities and publishing papers.