Found.dev
Role Highlights
Languages used
Python
Key skills
Deep Learning
Data Analysis
Feature Engineering
Machine Learning
Product Management
Critical Thinking
Cloud
AI
DataSets
Optimization
Reliability
Deployment
Statistics
Tools, Libraries and Frameworks
IOS
IBM
AWS
Azure
GCP
Tensorflow
PyTorch
Scikit-learn
Description
The role involves designing and developing AI and Generative AI models specifically for the healthcare and life sciences sectors. The professional will analyze large structured and unstructured datasets to derive actionable insights and support clinical decision-making. Collaboration with cross-functional teams, including clinicians and engineers, is required to integrate these solutions into existing workflows. The position includes developing predictive models for patient outcomes and implementing agentic AI systems to automate healthcare tasks. Additionally, the role requires conducting performance evaluations to ensure model reliability and maintaining documentation for regulatory compliance.
Required Qualifications and Skills
Candidates must possess proven experience in AI, Generative AI, and machine learning model development, specifically with deep learning and agentic systems. Proficiency in programming languages such as Python or R is required, alongside experience with frameworks like TensorFlow, PyTorch, and scikit-learn. Applicants need experience working with healthcare or life sciences data, including EHR or genomic datasets, and a solid understanding of statistics and experimental design. Familiarity with cloud platforms and the deployment of production-level AI solutions is also necessary. No specific degree or professional certification is explicitly mentioned as a requirement.
Disclaimer
Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.
About the company
IBM
Description
IBM infuses core business operations with intelligence, from machine learning to generative AI, to make organizations more responsive, productive, and resilient. It helps clients put AI into action now, creating real value with trust, speed, and confidence across various areas like digital labor, IT automation, and security. The ability to utilize all data is critical, as AI's effectiveness is dependent on the quality of data fueling it, with IBM's AI, and data platform aiming to scale and accelerate AI's impact with trusted data. IBM's hybrid cloud platform offers a comprehensive approach to development, security, and operations across hybrid environments, laying a flexible foundation for leveraging data wherever it resides.
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