Generative AI Engineer - Remote
Job Description
Grow your career at Cedars-Sinai!
The Enterprise Information Services (EIS) team at Cedars-Sinai understands that true clinical transformation and the optimization of a clinical information systems implementation is fueled through the alignment of the right people, processes, and technologies.
Why work here?
Cedars-Sinai placed in the top 20 on Newsweek's "World's Best Smart Hospitals 2024" list, which highlights hospitals that have excelled in the utilization of electronic functionalities, telemedicine, digital imaging, artificial intelligence and robotics.
The organization's Healthtech excellence was acknowledged again, this time by the esteemed "CHIME Digital Health Most Wired" recognition program. Cedars-Sinai was assigned a Level 10-the most prestigious level of certification-among more than 300 surveyed healthcare organizations. Cedars-Sinai netted high scores across multiple verticals and particularly excelled in areas of infrastructure, interoperability, and population health innovation.
What will you be doing in this role:
The Generative AI Engineer will have experience in fine-tuning and training neural networks, with a focus on generative models. You will be responsible for developing, implementing, and optimizing AI models to solve sophisticated problems and improve our product offerings.
• Design, build, and optimize generative neural network models using pioneering techniques.
• Perform fine-tuning of pre-trained models to cater to specific tasks and improve performance.
• Develop and implement robust training pipelines for AI models, ensuring scalability and efficiency.
• Stay up-to-date with the latest advancements in generative AI and neural network technologies, and apply this knowledge to improve existing models.
• Work closely with cross-functional teams including data scientists, software engineers, and product managers to integrate AI solutions into products.
• Conduct meticulous testing and evaluation of models, ensuring that they meet quality and performance standards.
• Maintain clear and comprehensive documentation of models, processes, and experimental results.
Qualifications
Experience Requirements:
Two (2) plus years of experience in developing and training neural networks with an emphasis on fine-tuning foundational models, CNNs, and transformer models.
Solid understanding of Python, app development paradigms and deep learning frameworks.
Experience with Reinforcement Learning is a plus.
Educational Requirements:
Bachelor's degree in Computer Science, Machine Learning, Applied Mathematics, Econometrics, Statistics, Engineering, Physics, or related discipline.
Master's degree preferred.
#LI-Remote
Apply Now
Apply Now
Grow your career at Cedars-Sinai!
The Enterprise Information Services (EIS) team at Cedars-Sinai understands that true clinical transformation and the optimization of a clinical information systems implementation is fueled through the alignment of the right people, processes, and technologies.
Why work here?
Cedars-Sinai placed in the top 20 on Newsweek's "World's Best Smart Hospitals 2024" list, which highlights hospitals that have excelled in the utilization of electronic functionalities, telemedicine, digital imaging, artificial intelligence and robotics.
The organization's Healthtech excellence was acknowledged again, this time by the esteemed "CHIME Digital Health Most Wired" recognition program. Cedars-Sinai was assigned a Level 10-the most prestigious level of certification-among more than 300 surveyed healthcare organizations. Cedars-Sinai netted high scores across multiple verticals and particularly excelled in areas of infrastructure, interoperability, and population health innovation.
What will you be doing in this role:
The Generative AI Engineer will have experience in fine-tuning and training neural networks, with a focus on generative models. You will be responsible for developing, implementing, and optimizing AI models to solve sophisticated problems and improve our product offerings.
• Design, build, and optimize generative neural network models using pioneering techniques.
• Perform fine-tuning of pre-trained models to cater to specific tasks and improve performance.
• Develop and implement robust training pipelines for AI models, ensuring scalability and efficiency.
• Stay up-to-date with the latest advancements in generative AI and neural network technologies, and apply this knowledge to improve existing models.
• Work closely with cross-functional teams including data scientists, software engineers, and product managers to integrate AI solutions into products.
• Conduct meticulous testing and evaluation of models, ensuring that they meet quality and performance standards.
• Maintain clear and comprehensive documentation of models, processes, and experimental results.
Qualifications
Experience Requirements:
Two (2) plus years of experience in developing and training neural networks with an emphasis on fine-tuning foundational models, CNNs, and transformer models.
Solid understanding of Python, app development paradigms and deep learning frameworks.
Experience with Reinforcement Learning is a plus.
Educational Requirements:
Bachelor's degree in Computer Science, Machine Learning, Applied Mathematics, Econometrics, Statistics, Engineering, Physics, or related discipline.
Master's degree preferred.
#LI-Remote
Apply Now
Apply Now