Support NBCUniversal’s advertising business by applying data science and machine learning to real‑world advertising and media challenges.
Compensation
The hourly rate for student interns is $30.00.
Responsibilities
Analyze large datasets using Python and SQL
Evaluate synthetic data and support media optimization projects
Collaborate with cross‑functional partners to develop advanced analytics and privacy‑safe data solutions
Translate technical findings into clear insights for business teams
Requirements
Pursuing a degree in a quantitative or technical field, such as Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field
Fraud analyst at CRED working at the intersection of data, technology and fraud prevention to identify and prevent emerging fraud patterns across products.
Responsibilities
Analyse large datasets to identify unusual patterns, behaviours and signals that could indicate emerging fraud
Investigate how fraudsters may be exploiting products, processes or system vulnerabilities
Develop hypotheses, test them through data and translate findings into practical fraud detection approaches
Work with data science and engineering to identify and close gaps in fraud detection and prevention
Identify new signals and approaches that can improve our ability to detect evolving fraud patterns
Build and deploy production‑grade machine learning software, tools, and infrastructure, collaborating with engineers, data scientists, and commercial leads to solve client challenges.
Responsibilities
Building and deploying production‑grade ML software, tools, and infrastructure
Creating reusable, scalable solutions that accelerate the delivery of ML systems
Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges
Leading technical scoping and architectural decisions to ensure project feasibility and impact
Defining and implementing Faculty’s standards for deploying machine learning at scale
Seeking a motivated software engineering intern to join a paid summer internship program focused on working on cutting-edge generative AI applications.
Compensation
estimated salary range for this position is $20.00 to $25.00
Responsibilities
Develop and integrate generative AI solutions using LLMs and APIs
Build web applications with AI-powered features
Write clean, maintainable code following best practices
Collaborate with senior engineers on product development
Test and debug AI applications
Requirements
Bachelor or Master’s Computer Science or related field
Enrolled in Graduate program or in the last year of Undergraduate degree
AI Engineer – Forward Deployed Engineer (FDE) to design, build, deploy, and operationalize AI solutions directly within customer environments, combining AI/ML and Generative AI engineering with customer engagement.
Responsibilities
Work directly with customers and business stakeholders to understand complex use cases and translate them into AI/GenAI solutions.
Design, develop, and deploy production-grade applications using Large Language Models (LLMs) and machine learning technologies.
Build Retrieval-Augmented Generation (RAG) pipelines using enterprise data sources, embeddings, vector databases, and semantic search.
Develop AI agents and agentic workflows, including tool calling, orchestration, memory, and multi-step reasoning patterns.
Integrate AI capabilities with enterprise applications, APIs, databases, cloud platforms, and existing business workflows.
Requirements
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field
The AI Technical Product Manager bridges the gap between artificial intelligence capabilities and real-world product applications, combining deep technical understanding with strategic product understanding to build AI-powered solutions that deliver measurable value.
Compensation
This position is salary grade level 058. Please visit Harvard's Salary Ranges to view the corresponding salary range and related information.
Responsibilities
Balance innovation with practical implementation, assessing technical feasibility and business impact
Establish success metrics and KPIs for AI product initiatives
Collaborate with data scientists, ML engineers, and software developers to translate business requirements into technical specifications
Understand AI/ML fundamentals including model architectures, training processes, evaluation metrics, and deployment considerations
Make informed decisions about model selection, data requirements, and infrastructure needs
Requirements
Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field
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