staff ai EngineerCông ty CP Doctor Anywhere Việt Nam

Mô tả công việc
Tóm tắt công việc
About the team
The AI team at Doctor Anywhere (DA) is dedicated to maximizing the positive impact of AI products for users and patients across the Southeast Asia (SEA) region. At the heart of the team's mission is the development of innovative AI solutions that not only simplify healthcare service delivery and elevate patient experiences but also assist doctors and automate internal workflows for efficiency. This team works closely with product managers, software engineers, designers, and relevant business functions to develop a deep understanding of how the products can be developed and delivered.
About the role
We are seeking an experienced and hands-on Staff AI Engineer to join our dynamic team. As a Staff AI Engineer, you play a pivotal role in shaping our AI strategy and driving next-generation technology (such as Generative AI) in building a vertically integrated digital healthcare ecosystem across Southeast Asia.
You will report directly to our CTO.
Act as an advisor to our founder, CTO and stakeholders to define our AI strategy.
Create a roadmap for AI research, development, and model deployment.
Partner with our AI team in designing, implementing, and optimizing machine learning models (especially large language models).
Utilize both external and proprietary machine learning tools and infrastructure to build adaptable, high-performance machine learning systems that facilitate rapid model development, efficient real-time deployment, and straightforward maintenance of model quality.
Closely collaborate with our engineering teams to ensure smooth end-to-end delivery of AI solutions.
Work closely with our infrastructure engineering team to build and leverage machine learning infrastructure to ensure that machine learning models run smoothly, scale effectively and deliver valuable insights.
Collaborate with our data team to understand data requirements. Clean, preprocess, and transform large scale structured and unstructured data for model training.
Rapidly prototype AI solutions, iterate, and learn from failures.