Lead AI research and technical strategy for medical imaging and Physical AI systems, driving end-to-end development from concept to clinical deployment.
Responsibilities
Define and own long-term research vision for medical image analysis and Physical AI-enabled imaging systems
Architect and lead development of state-of-the-art detection, segmentation, classification, reconstruction, and quantitative imaging systems
Drive innovation in vision and multimodal transformers, large-scale foundation models, self-supervised learning, physics-informed ML, and simulation-to-real transfer
Establish technical standards for experimental rigor, physical robustness, uncertainty quantification, clinical validation, fairness, and generalization
Partner with clinicians, radiologists, pathologists, imaging scientists, and regulatory stakeholders to formulate AI problem statements
Requirements
PhD in Computer Science, Electrical Engineering, Biomedical Engineering, Applied Physics, Robotics, or a closely related field
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution.
Responsibilities
Expected to be an SME, collaborate and manage the team to perform.
Responsible for team decisions.
Engage with multiple teams and contribute on key decisions.
Provide solutions to problems for their immediate team and across multiple teams.
Lead the development and deployment of AI models ensuring scalability and reliability.
As an AI / ML Engineer, a typical day involves designing and building advanced applications and systems that leverage artificial intelligence technologies and cloud-based AI services. The role requires ensuring that these solutions are production-ready, whether deployed on cloud platforms or on-premises. The engineer integrates generative artificial intelligence models into various projects, which may encompass deep learning techniques, neural network architectures, conversational agents, and image processing tasks.
Responsibilities
Be an SME, collaborate and manage the team to perform
Responsible for team decisions
Engage with multiple teams and contribute on key decisions
Provide solutions to problems for their immediate team and across multiple teams
Lead the development and deployment of AI models ensuring scalability and reliability
Plan and perform rapid prototyping of computer vision and multimodal machine learning techniques applied to determining authenticity of media information.
Design and train multimodal models capable of complex visual reasoning.
Undertake exploratory analysis to inform experimentation and research directions.
Engage with product teams to drive the development of our research.
Report and present research findings, software developments, experimental results, and data analysis clearly and efficiently.
Requirements
UNIV - Postdoctoral Scholar - Department of PHS
Medical University of South Carolina · Posted Nov 10, 2026
Postdoctoral researcher in clinical AI and digital health to join the Division of Biomedical Informatics & AI at MUSC.
Compensation
Pay Range 0.00 - 0.00 - 0.000
Responsibilities
Acquire, curate and preprocess EHR, clinical notes, wearable and mobile data, and design, train and evaluate machine learning, deep learning and language models.
Lead analyses and first-author manuscripts for peer-reviewed journals and conferences, and present findings at national meetings.
Contribute to NIH grant proposals, including preliminary data and aims development.
Work with collaborators to define clinically meaningful outcomes and validate models.
Help mentor graduate and undergraduate students in the lab.
Requirements
PhD in biomedical informatics, computer science/engineering, data science, biomedical engineering, biostatistics or a related field
Nice to have: Interest in pursuing a K award or other early-career funding
Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution.
Responsibilities
Expected to perform independently and become an SME.
Required active participation/contribution in team discussions.
Contribute in providing solutions to work related problems.
Collaborate with team members to continuously improve AI model performance and deployment strategies.
Assist in documenting technical processes and sharing knowledge to support team growth and project continuity.
Research scientist to advance multimodal foundation model architectures, pre‑training, and distillation for Apple.
Locations (2)
Seattle, Washington, United States
Sunnyvale, California, United States
Responsibilities
Investigate fundamental questions about multimodal foundation model design, training, and distillation
Develop and evaluate new model architectures, pre‑training objectives, data strategies, optimization methods, and teacher–student learning techniques
Co‑develop frontier models and efficient models for Apple silicon and on‑device intelligence
Design architectures that distill effectively and study teacher–student training
Develop distillation methods that preserve reasoning, multimodal understanding, instruction following, and other capabilities under constrained model capacity
Requirements
Master’s degree in machine learning, computer science, or a related technical field
AI Research Scientist: Multimodal Foundation Models - Architecture, Pre-Training & Distillation
Lead product strategy and roadmap for AI infrastructure stack, defining compiler, runtime, and framework integration features.
Responsibilities
Translate customer, engineering, and business requirements into detailed Product Requirements Documents (PRDs), technical specifications, and feature definitions.
Develop detailed product schedules, milestone plans, and release timelines while managing dependencies across multiple engineering organizations.
Define requirements for the software and AI model compilation toolchain.
Lead product partnerships and technical integrations with major machine learning frameworks and runtimes.
Define performance optimization roadmap for low-level operator libraries.
Requirements
Master of Science (M.Sc.) in Computer Science, Electrical Engineering, Mathematics, or Physics
Doctor of Philosophy (Ph.D.) in Computer Science, Electrical Engineering, Mathematics, or Physics
Nice to have: MBA
Nice to have: open-source AI infrastructure contributions
Lead product management for AI infrastructure stack, defining roadmap for compiler, runtime, and framework integration.
Responsibilities
Translate customer, engineering, and business requirements into detailed Product Requirements Documents (PRDs), technical specifications, and feature definitions.
Develop detailed product schedules, milestone plans, and release timelines while managing dependencies across multiple engineering organizations.
Define requirements for the software and AI model compilation toolchain.
Lead product partnerships and technical integrations with major machine learning frameworks and runtimes.
Define performance optimization roadmap for low-level operator libraries.
Requirements
Master of Science (M.Sc.) in Computer Science, Electrical Engineering, Mathematics, or Physics
Doctor of Philosophy (Ph.D.) in Computer Science, Electrical Engineering, Mathematics, or Physics
Nice to have: MBA
Nice to have: open-source AI infrastructure contributions
Senior Research Engineer, Multimodal Reasoning and Media ForensicsNewGoogle · Mountain View, US+1 more
AI Research Scientist: Multimodal Foundation Models - Architecture, Pre-Training & DistillationNewApple · Seattle, US+1 more