Speechmatics | AI Voice Agents
Mini tools
Data Scientist - AI Agent
Verily
On-site
San Bruno, CA, United States
Full-time
$140,000 -
$200,000
About Verily
Verily is a subsidiary of Alphabet that is using a data-driven approach to change the way people manage their health and the way healthcare is delivered. Launched from Google X in 2015, our purpose is to bring the promise of precision health to everyone, every day. We are focused on generating and activating data from a variety of sources, including clinical, social, behavioral and the real world, to arrive at the best solutions for a person based on a comprehensive view of the evidence. Our unique expertise and capabilities in technology, data science and healthcare enable the entire healthcare ecosystem to drive better health outcomes.
About the Role
As an AI and Data Scientist at Verily, you will be supporting our core mission to build advanced data and AI capabilities for Verily's portfolio of products, which serve both consumer and business audiences. You will help drive innovation in data-driven healthcare by developing and deploying sophisticated models into our products.
This role requires a blend of applied science and product-focused creativity; you should expect to conduct research and innovate on new methods to directly support and enhance our product offerings. Using cutting-edge techniques, you will analyze complex datasets to build robust solutions and collaborate with a diverse cross-functional team to build reusable and scalable tools that unlock information from structured and unstructured clinical data.
This role requires a blend of applied science and product-focused creativity; you should expect to conduct research and innovate on new methods to directly support and enhance our product offerings. Using cutting-edge techniques, you will analyze complex datasets to build robust solutions and collaborate with a diverse cross-functional team to build reusable and scalable tools that unlock information from structured and unstructured clinical data.
Qualifications
Advanced degree in a quantitative discipline (e.g., statistics, computer science, applied mathematics, or similar) or equivalent practical experience.
Experience with applying ML in digital health applications.
Direct experience working with LLM and familiar with various prompt optimization technologies.
Preferred Qualifications
Ph.D. in Computer Science or Engineering.
Experience with LLM models, including prompting, fine-tuning and retrieval augmented generation (RAG).
Familiarity with software engineering principles and experience deploying algorithms in production environments.
Experience developing transformer based deep learning algorithms using TensorFlow or PyTorch, and knowledge of latest architectures.
Experience with applying ML in digital health applications.
Direct experience working with LLM and familiar with various prompt optimization technologies.
Preferred Qualifications
Ph.D. in Computer Science or Engineering.
Experience with LLM models, including prompting, fine-tuning and retrieval augmented generation (RAG).
Familiarity with software engineering principles and experience deploying algorithms in production environments.
Experience developing transformer based deep learning algorithms using TensorFlow or PyTorch, and knowledge of latest architectures.
Responsibilities
Collaborate with cross-functional teams to conceptualize, develop, and implement AI solutions tailored to diverse healthcare applications.
Architect and implement foundational models and large language model (LLM) based agents to achieve optimal performance and efficiency.
Conduct cutting-edge research and stay informed on emerging advancements in LLMs, medical foundational models, and AI agents.
Effectively communicate complex technical methodologies and results through clear, well-structured reports and presentations for both technical and non-technical audiences.
Architect and implement foundational models and large language model (LLM) based agents to achieve optimal performance and efficiency.
Conduct cutting-edge research and stay informed on emerging advancements in LLMs, medical foundational models, and AI agents.
Effectively communicate complex technical methodologies and results through clear, well-structured reports and presentations for both technical and non-technical audiences.
