761 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" positions at Northeastern University
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 28-Dec-25 Location: Boston, Massachusetts Type: Full-time Categories: Academic/Faculty Computer/Information Sciences
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, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more information. All qualified applicants are encouraged to apply
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https://hr.northeastern.edu/benefits/ for more information. All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color
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About the Opportunity About Northeastern: Founded in 1898, Northeastern is a global research university and the recognized leader in experience-driven lifelong learning. Our world-renowned
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computer skills, including the Microsoft Office suite of products and internet research. Key Responsibilities Prospect Identification Develop and oversee execution of ongoing screening schedule
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emphasis on applied machine learning, artificial intelligence and experiential network addressing the business challenges in the industry. Instructional areas include, but are not limited to, analytics, with
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research, teaching, and engagement missions, the college collaborates across the university, the Northeastern network, and partners around the globe. Responsibilities: Teach European, World, or American
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and written communication skills with a customer (internal and external) service focus Strong computer and IT skills, especially in MS Office suite products, and ability to learn new programs/systems
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collaborate with academic and industry partners of EAI. Minimum Qualifications: An MS in computer science with a heavy focus on machine learning and LLM-RAG construction and development by the appointment start
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engineering service offerings. Other necessary skills: MLOps Experience: Demonstrated experience in operationalizing and maintaining machine learning models in production environments, including deployment