高级 AI/ML 工程师 - 生命科学
Sr. AI/ML Engineer- Life Sciences
Abbott 是一家全球医疗健康领导者,帮助人们在生命各个阶段更好地生活。我们的产品组合涵盖改变生命的医疗技术,业务和产品覆盖诊断、医疗设备、营养品和品牌仿制药领域。我们的 122,000 名员工服务于 160 多个国家的客户。
职位描述:
职位概述
高级 AI/机器学习工程师负责指导生命科学 AI 平台的架构、技术路线图以及实际实现,为科学和医学部门的代理解决方案提供基础。该职位协助塑造组织的 AI 战略,并评估新兴的最先进技术,以在平台上进行实际应用。该职位服务的对象包括生物信息学、生物统计学和数据科学团队中的技术用户,以及临床事务、法规事务和医学运营部门中的非技术用户,工作环境涉及先进的癌症筛查和精准肿瘤学。这项工作结合务实的实验与明确的原型之外的路径,产出经过评估、验证、管理、支持并可重复使用解决方案。该职位定义生成式 AI 解决方案开发和发布的工程标准、控制和验证框架,并通过指导和架构评审提供技术领导力。
主要职责
包括但不限于以下内容:
- 指导生命科学生成式 AI 平台的架构、技术路线图和战略演进,包括其运行时、网关、内存、身份识别、可观测性和评估能力,以加速和改善科研和医疗流程及结果。
- 设计和实现共享平台服务、可重用组件和支持的解决方案模式,概括常见需求并减少对功能特定点解决方案的依赖。
- 使用安全、受支持的平台模式,将代理框架和互操作协议与企业数据源、文档仓库和科学系统集成。
- 与跨科学和医疗职能的干系人和 AI/ML 工程师合作,将操作流程、标准操作程序和业务需求转化为可扩展、受支持的 AI 解决方案。
- 通过定义和应用展示解决方案质量、可靠性、效率和商业价值的评估标准,推动平台的采用。
- 应用敏捷实践,迭代开发、评估和部署解决方案,确保符合业务目标和技术要求。
查看英文原文
Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries.JOB DESCRIPTION:
Position Overview
The Sr.AI/MLEngineerguidesthe architecture, technical roadmap, and hands-on implementation of thelife sciencesAI platformproviding the foundations for agentic solutions across the science and medical offices.This role helps shape the organization’s AI strategy and evaluates emerging state-of-the-art technologies for practical implementation within the platform.This role serves both technical consumers intheBioinformatics,Biostatistics and Data Science group,and non-technical consumers across Clinical Affairs, Regulatory Affairs, and Medical Operationswithin a setting of advanced cancer screening and precision oncology.The work combines pragmatic experimentation with a clear path beyond prototypes, producing solutions that are evaluated, validated, governed, supported, and reusable.This role defines the engineering standards, controls, and validation framework under whichgenerativeAI solutions are developed andpublished, andprovides technical leadership through mentorship and architecture review.
Essential Duties
Include, but are not limited to, the following:
- Guidethe architecture, technical roadmap, and strategic evolution of thelife sciencesgenerativeAI platform, including its runtime, gateway, memory, identity, observability, and evaluation capabilities, to accelerate and improve scientific and medical processes and outcomes.
- Design and implement shared platform services, reusable components, and supported solution patterns that generalize recurring needs and reduce reliance on function-specific point solutions.
- Integrate agent frameworks and interoperability protocols with enterprise data sources, document repositories, and scientific systems using secure, supported platform patterns.
- Partner with stakeholders and AI/ML engineers across science and medical functions to translate operational workflows, SOPs, and business needs into scalable, supported AI solutions.
- Driveplatformadoption bydefining and applying evaluation criteria that demonstrate solution quality, reliability, efficiency, and business value.
- Apply Agile practices to iteratively develop, evaluate, and mature promising concepts into validated, reusable solutions.
- Provide mentorship and coaching to more junior level team members.
- Act as resource and subject matter expert in core team and/or cross-functional meetings.
- Communicate difficult, sensitive, and complex information clearly to technical and non-technical stakeholders.
- Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
- Support and comply with the company’s Quality Management System policies and procedures.
- Maintain regular and reliable attendance and availability during the designated work schedule.
- Act with an inclusion mindset and model these behaviors for the organization.
- Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 85% of a typical working day.
- Ability to travel 5% of working time away from work location, may include overnight/weekend travel.
Minimum Qualifications
- Ph. Din Statistics, Computational Biology, Computer Science, or related quantitative field as outlined in the essential duties, or master’s degree in Statistics, Computational Biology, Computer Science, or related quantitative field as outlined in the essential duties plus 4 years of experience in lieu of a Ph.D.
- 3+ years of experience in statistics, computational biology, applied mathematics, or related quantitative field as outlined in the essential duties.
- 3+ years of experience with artificial intelligence and machine learning algorithms.
- Demonstrated knowledge and experience with advanced AI concepts, such as artificial neural networks, deep learning, and reinforcement learning.
- Demonstrated knowledge and experience using artificial intelligence and machine learning techniques within one or more of the following fields: natural language processing, image processing and computer vision, image and pattern recognition.
- Demonstrated knowledge and experience with large language models for generative AI and associated concepts, such as transformer architecture and retrieval augmented generation.
- Strong programming ability with demonstrated experience in Python and one or more associated machine learning frameworks, such as TensorFlow,PyTorch, orSKLearn.
- Knowledge of and experience working with open-source AI models.
- Demonstrated ability to perform the essential duties of the position with or without accommodation.
- Authorization to work in the United States without sponsorship.
Preferred Qualifications
- 2+ years of life sciences industry experience working with biological data.
- 2+ years of industry experience in molecular diagnostics, preferably cancer diagnostics.
- Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data.
- Basic knowledge of ML-Ops and processes for managing the versioning and deployment of machine learning models.
- Scientific understanding of cancer biology
The base pay for this position is
$78,000.00 – $156,000.00In specific locations, the pay range may vary from the range posted.
JOB FAMILY:
Product DevelopmentDIVISION:
ONCO Cancer DiagnosticsLOCATION:
United States of America : RemoteADDITIONAL LOCATIONS:
WORK SHIFT:
StandardTRAVEL:
Yes, 5 % of the TimeMEDICAL SURVEILLANCE:
Not ApplicableSIGNIFICANT WORK ACTIVITIES:
Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day), Keyboard use (greater or equal to 50% of the workday)Abbott is an Equal Opportunity Employer of Minorities/Women/Individuals with Disabilities/Protected Veterans.EEO is the Law link - English: is the Law link - Espanol: Originally posted on Himalayas