Research Engineer - R&D Internship – 2027 Yorktown Heights & Cambridge will join the Software Innovation Lab team to advance state-of-the-art agent architectures and domain-specific models. Working in mentored teams, the intern will build, test, and deploy real-world applications for business processes, IT, industrial automation, and software engineering across distributed and non-distributed environments. Key responsibilities include translating cutting-edge AI techniques into practical solutions, developing enterprise-grade benchmarks, and disseminating results through publications and patent applications. The role requires strong programming skills in Python, familiarity with machine learning fundamentals, natural language processing, and generative AI. Candidates should possess experience with deep learning frameworks and rigorous experimental evaluation. This work addresses the technical challenge of personalizing services, automating operations, and optimizing workflows within complex enterprise environments.
Advance state-of-the-art agent architectures and domain-specific models for business processes and industrial automation.
Develop responsible AI systems and enterprise-grade benchmarks to personalize services and optimize workflows.
Translate cutting-edge AI techniques into practical solutions for enterprise and user-facing applications.
Build and deploy AI tools and platforms across distributed and non-distributed environments.
Shepherd research projects from the initial ideation phase through to final completion.
Disseminate significant research results through publications in leading conferences and patent applications.
Contribute to IBM's open innovation initiatives and academic community engagement.
What we're looking for
High School Diploma/GED.
Master's Degree (preferred).
Currently pursuing a degree in Computer Science, Engineering, or a related field (BS/MS).
Strong programming skills in Python.
Familiarity with machine learning fundamentals, natural language processing, and generative AI.
Strong problem-solving mindset and ability to work in a collaborative team environment.
Strong foundations in machine learning and software engineering with hands-on experience in deep learning frameworks and rigorous experimental evaluation (preferred).
Prior experience with open-source contributions, research projects, or AI-related hackathons (preferred).
Python
PyTorch
Generative AI
LLMs
Multimodal AI
Foundation Models
Agentic Systems
Knowledge Graphs
Distributed Systems
Continual Learning
Machine Learning
AI Security
Hybrid Cloud
Data Science
Machine Learning
AI
Quantum Computing
High Performance Computing
Hybrid Cloud
Computer Science
Data Analysis
Semiconductor Research
Chip Architecture
Material Science
Physics
Chemistry
Mechanical Engineering
Python
MATLAB
C
C++
R
AWS ML
Microsoft Azure ML
Machine Learning
Deep Learning
Data Science
Computer Vision
Artificial Intelligence
Big Data
Object-Oriented Design
Design Patterns
Statistics
Robotics
Additive Manufacturing