Senior AI/ML Engineer – Life Science

🔥 1 minute ago

🇺🇸 United States – Remote

💵 $99.3k - $198.7k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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Abbott

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1888

🏥 Healthcare

⚕️ Healthcare Insurance

🧬 Biotechnology

Healthcare • Healthcare Insurance • Biotechnology

Abbott is a global healthcare company committed to advancing medical technologies and improving lives around the world. It offers a broad range of leading products in diagnostics, medical devices, nutrition, and branded generic medicines. Abbott's innovations such as the FreeStyle Libre glucose monitoring systems and BinaxNOW rapid antigen tests are transforming diabetes management and COVID-19 response. Through its partnerships and initiatives, Abbott aims to foster health equity, improve access to healthcare, and address critical health challenges like malnutrition and infectious diseases. Abbott is also dedicated to sustainability and social responsibility, striving to make life-changing technologies accessible and affordable.

📋 Description

• Lead development of perspectives on AI technology affordances • Identify, refine, prioritize, and formalize requirements for ML- and AI-based solutions focused on bioinformatics, biostatistics, and data engineering • Provide technical and strategic leadership for software solutions using advanced AI and ML techniques • Lead implementation and deployment of ML and AI solutions with AI/ML and software engineers • Establish an Agile framework for iterative rapid solutions • Develop AI strategy to accelerate and enhance bioinformatics, biostatistics, and data science processes • Lead training resources, knowledge bases, and education on advanced AI/ML technologies and best practices • Lead AI evangelism for biostatistics, bioinformatics, and data science • Solve complex problems using sophisticated analytical judgment and innovative solutions • Mentor and coach junior team members • Serve as a subject matter expert in core and cross-functional meetings • Contribute innovative ideas to the intellectual property portfolio • Communicate complex information and influence decision-making • Uphold company mission and values and comply with the Quality Management System

🎯 Requirements

• Ph.D in Statistics, Computational Biology, Computer Science, or related quantitative field, or Master’s Degree in one of these fields plus 4 years of relevant experience • 5+ years of experience in statistics, computational biology, applied mathematics, or related quantitative field • 5+ years of experience with artificial intelligence and machine learning algorithms • Mastery of artificial neural networks, deep learning, and reinforcement learning • Mastery of AI/ML techniques in natural language processing, image processing and computer vision, or image and pattern recognition • Mastery of large language models for generative AI, transformer architecture, and retrieval augmented generation • Strong programming ability in Python and one or more ML frameworks such as TensorFlow, PyTorch, or SKLearn • Knowledge and experience working with open-source AI models • Excellent communication skills and ability to explain complex topics to varied audiences • Ability to perform essential duties with or without accommodation • Authorization to work in the United States without sponsorship • Preferred: 8+ years of life sciences industry experience working with biological data • Preferred: 8+ years of industry experience in molecular diagnostics, preferably cancer diagnostics • Preferred: Expertise in healthcare data mining • Preferred: Basic knowledge of MLOps and model versioning/deployment • Preferred: Scientific understanding of cancer biology • Ability to work designated schedule • Ability to work on a mobile device, tablet, or computer and type for approximately 85% of a typical working day • Ability to act with an inclusion mindset • Regular and reliable attendance

🏖️ Benefits

• Travel opportunity: 5% of working time away from work location, potentially including overnight/weekend travel