Harvard Business Publishing (HBP) is looking to drive innovation and enhance product offerings through the application of AI and ML technologies to improve the practice of management in a changing world.
Requirements
- Experience: 5+ years in data science, ML/AI development, or a closely related field, with a proven track record of delivering production-grade AI/ML solutions
- ML Infrastructure: Hands-on experience with developing, deploying, and maintaining ML infrastructure, including model training, evaluation, and production-ready APIs.
- Programming Skills: Excellence in Python programming and experience with relevant data science and AI/ML packages such as pandas, scikitlearn, pytorch, and Langchain.
- Cloud Services: Practical experience with cloud services such as AWS (preferred), Azure, or Google Cloud for deploying and managing AI/ML workflows and containerization tools like docker
- Gen AI experience: 3+ years of experience developing products with, and guardrails for, LLMs strongly preferred
- No-Code AI Tools: Experience support end users of no-code AI-assistive tools and platforms and ability to support transitions of no-code prototypes to dev and production environments
- Data Engineering: Familiarity with data engineering concepts and tools, including data pipelines, ETL processes, data warehousing, the medallion architecture, and dbt
Responsibilities
- Support product teams in building new AI-enabled features: Contribute to technical vision and participate directly as a technical resource in product development, focusing on innovation with data and AI to create cutting-edge solutions.
- Facilitate technical interoperability: Act as a bridge between HBP product management, data engineering, production software engineering, and partner technical teams at HBP and HBS to extend and leverage core ML and AI infrastructure across development stages from prototyping to production
- Develop and maintain ML and AI infrastructure: Work in consultation with partner technical teams at HBP and HBS to develop and maintain the infrastructure needed for product-facing ML and AI applications, such as an LLM chat interface, a vector store for RAG, predictive ML workflows with automated triggers, and ML Ops tools, within AWS and snowflake environments
- Contribute to data engineering: Ensure quality and integrity of user, content, and market data by collaborating with the Data Engineering team to build and maintain data pipelines and product-facing APIs for HBP's central data warehouse relevant to products the AID is supporting
- Support data science and analytics: Contribute to design and execution of data science and analytics projects relevant to products the AID is supporting, such as inferring causal factors driving user intent, predicting user attributes, exposing insight from user activity to inform editorial and marketing decisions, and projecting potential revenue
Other
- Collaboration: Excellent communication and stakeholder management skills, with the ability to work effectively across multiple teams and departments.
- Innovation: A strong passion for innovation and the ability to think creatively about how AI and ML can be applied to solve business problems and enhance product offerings
- Education reimbursement and early-release Summer Fridays!
- Annual Performance Based Variable Pay Program
- Equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions, or any other characteristic protected by law
