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EBSCO Information Services Solution Specialist, AI & Machine Learning in Boston, Massachusetts

EBSCO Information Services (EBSCO) delivers a fully optimized research experience, seamlessly integrated with a powerful discovery platform to support the information needs and maximize the research experience of our end-users. Headquartered in Ipswich, MA, EBSCO employs more than 2,700 people worldwide, with most embracing hybrid or remote work models. As an AI-enabled service leader, we thrive on innovation, forward-thinking strategies, and the dedication of our exceptional team. At EBSCO, we’re driven to inspire, empower and support research. Our mission is to transform lives by providing reliable and relevant information — when, where and how people need it. We’re seeking dynamic, creative individuals whose diverse perspectives will help us achieve this global, inclusive mission. Join us to help make an impact.

Your Opportunity

You are an information specialist who relishes solving novel problems in the areas of machine learning, generative AI, natural language processing, information extraction, document summarization, information retrieval, search relevancy, and/or knowledge graphs. You will bring new ideas, iterate quickly, share findings, and drive new solutions for content metadata enrichment, search analytics, and content discovery/findability.

This job is not a traditional software developer or data science role and is best suited to someone with knowledge and experience in fields such as information systems, knowledge management, and/or library science.

This remote position is U.S.-based only (excluding U.S. territories).

What You'll Do

  • Develop tools and strategies leveraging text analytics, machine learning, generative AI, and metadata enrichment pipelines

  • Analyze and interpret search data to identify patterns, inform relevancy tuning, and support iterative improvements in search

  • Maintain and optimize knowledge graphs supporting content enrichment pipelines, advanced search methods, and new product functionality

  • Engineer precise, clear, and effective prompts to guide AI models towards generating desired outcomes and insights, while minimizing biases and hallucinations

  • Prototype new product functionality that demonstrates the power and value new technologies can bring to improve existing EIS products and platforms

  • Drive, design, and develop projects as the principal point-of-contact, with the ability to determine suitable MLAI models, leverage knowledge graphs, direct feature engineering, and negotiate KPIs per business needs

  • Develop and maintain strong working relationships across departments and with key partners and stakeholders, including business leaders, software developers, and knowledge engineers

  • Participate in special projects and perform other duties as assigned

Your Team

You will be welcomed as a member of the Semantic Enrichment team (a team of about 20 people) and the larger Product Management organization. Our team enjoys the flexibility and greater work life balance working remotely offers. There will be ample resources, tools, training, and support to ensure your success as a Senior Semantic Enrichment Specialist II and your development and career growth at EIS.

About You

  • 7 years' experience with natural language processing and/or machine learning model implementation

  • 7 years' experience with data processing, including extraction, transformation, and loading (ETL) of large data sets from unstructured and semi-structured data (plaintext, PDF, JSON, XML)

  • 7 years' experience with Python for data science, including Pandas, Jupyter notebooks, and open-source machine learning modules (Scikit, NLTK, Spacy)

  • 7 years’ experience in search analytics/relevancy tuning evaluation, ontologies/knowledge graphs, or a mix of both

What Sets You Apart

  • Experience working with generative AI models, including prompt engineering and parameter tuning

  • Advanced Python skills, including object-oriented programming, unit testing, and scripts in production

  • Advanced machine learning skills, including deep learning, large language models, model architectures, parameters, and ensemble modeling

  • Knowledge of MLOps processes including versioning, experimentation, deployment, and quality review

  • Understanding publishing industry perspectives and the needs of libraries and librarians

  • Bachelor's degree in information science, computer science or related technical field or equivalent experience

Pay Range

USD $109,800.00 - USD $156,855.00 /Yr.

The actual salary offer will carefully consider a wide range of factors including your skills, qualifications, education, training, and experience, as well as the position’s work location.

EBSCO provides a generous benefits program including:  

-Medical, Dental, Vision, Life and Disability Insurance and Flexible spending accounts  

-Retirement Savings Plan

-Paid Parental Leave 

-Holidays and Paid Time Off (PTO) 

-Mentoring program 

And much more! Check it out here: https://www.ebsco.com/about/benefits

We are an equal opportunity employer and comply with all applicable federal, state, and local fair employment practices laws. We strictly prohibit and do not tolerate discrimination against employees, applicants, or any other covered persons because of race, color, sex, pregnancy status, age, national origin or ancestry, ethnicity, religion, creed, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, training, promotion, discipline, compensation, benefits, and termination of employment.

We comply with the Americans with Disabilities Act (ADA), as amended by the ADA Amendments Act, and all applicable state or local law.

Not seeing the perfect job?

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Experienced Talent Community (https://talent.ebsco.com/exp/talentcommunity/form)

Early Career/Intern Talent Community

Location US-Remote

ID 2025-1706

Category Content Management

Position Type Full-Time Regular

Remote Yes

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