AI Foundations - Research Scientist

IBM; Cambridge (MA); On-site; USD 150,000 - 210,000; Full time

Job summary

IBM Research is seeking a Research Scientist in Artificial Intelligence to lead cutting-edge AI/ML projects and translate theoretical advances into practical systems. You will publish in top venues and collaborate with world-class scientists to push the boundaries of AI across domains, from deep learning to applicable quantum-inspired approaches.

The role emphasizes rigorous experimentation, verification of algorithm properties, and integration of AI techniques into scalable products and

Qualifications

• Deep expertise in one or more AI/ML areas including deep learning, RL, symbolic learning, CV, NLP, and related fields.
• Experience developing and proving mathematical properties of algorithms and evaluating their user impact.
• Proficiency with PyTorch and TensorFlow to develop AI solutions.
• Experience communicating research findings through publications in top conferences/journals.

Responsibilities

• Lead AI projects in deep learning, reinforcement learning, lifelong learning, and related areas.
• Develop and prove mathematical properties of algorithms and assess their impact on user experiences.
• Embed research algorithms into usable systems with seamless integration.
• Publish research findings in top-tier conferences and journals (e.g., NIPS, CVPR, ICML, ICLR).
• Leverage AI frameworks to develop and implement AI solutions.

Skills

Deep AI/ML expertise

Algorithm development

AI Frameworks: PyTorch, TensorFlow

Research communication

System integration of AI in usable ssy

Education

Doctorate Degree

Tools

PyTorch

TensorFlow

Job description

Introduction

At IBM Research, we are the innovation engine of IBM. Exploring what’s next in computing and shaping the technologies the world will rely on tomorrow. From advancing AI and hybrid cloud to pioneering practical quantum computing, we anticipate challenges and unlock new opportunities for clients, partners, and society. Working in Research means joining a team that accelerates discovery at the intersection of high-performance computing, AI, quantum, and cloud. You’ll collaborate with leading scientists, engineers, and visionaries to push boundaries and turn ideas into reality. With a culture built on curiosity, creativity, and collaboration, IBM Research offers the opportunity to grow your career while contributing to breakthroughs that transform industries and change the world.

Introduction

At IBM Research, we are the innovation engine of IBM. Exploring what’s next in computing and shaping the technologies the world will rely on tomorrow. From advancing AI and hybrid cloud to pioneering practical quantum computing, we anticipate challenges and unlock new opportunities for clients, partners, and society. Working in Research means joining a team that accelerates discovery at the intersection of high-performance computing, AI, quantum, and cloud. You’ll collaborate with leading scientists, engineers, and visionaries to push boundaries and turn ideas into reality. With a culture built on curiosity, creativity, and collaboration, IBM Research offers the opportunity to grow your career while contributing to breakthroughs that transform industries and change the world.

Your Role And Responsibilities

As a Research Scientist in Artificial Intelligence, you will lead cutting-edge projects in various AI and machine learning areas, creating and leveraging AI techniques to solve analytical problems using rigorous and quantitative approaches. You will also communicate your research in technical communities through publications in top‑tier conferences and journals.

Your primary responsibilities will include:

• Lead AI Projects: Lead projects in deep learning, reinforcement learning, lifelong learning, and other AI/ML areas, creating and applying AI techniques to solve complex analytical problems.
• Develop and Prove Algorithms: Develop and prove mathematical properties of algorithms, conducting successful experiments to demonstrate these properties and evaluating their impact on user experiences.
• Embed Research in Systems: Embed research algorithms in usable systems, ensuring seamless integration and effective application of AI techniques.
• Communicate Research: Communicate research findings through publications in top‑tier conferences and journals, such as NIPS, CVPR, ICML, and ICLR.
• Leverage AI Frameworks: Utilize frameworks like PyTorch,Tensorflow, to develop and implement AI solutions.

Preferred Education

Doctorate Degree

Required Technical And Professional Expertise

• Deep Expertise in AI/ML: Deep expertise in one or more AI/ML areas, including deep learning, reinforcement learning, lifelong learning, transfer learning, few‑shot learning, interpretable and adversarial learning, learning with memories, KRR, symbolic and trainable logic, causal inference, computer vision, speech, NLP, brain‑inspired algorithms, and neuromorphic architectures.
• Proven Algorithm Development: Experience with developing and proving mathematical properties of algorithms, conducting successful experiments to demonstrate these properties, and evaluating their impact on user experiences.
• AI Framework Proficiency: Proficiency in utilizing frameworks like PyTorch,Tensorflow, to develop and implement AI solutions.
• Research Communication: Experience with communicating research findings through publications in top‑tier conferences and journals, such as NIPS, CVPR, ICML, and ICLR.
• System Integration: Experience with embedding research algorithms in usable systems, ensuring seamless integration and effective application of AI techniques.

Preferred Technical And Professional Experience

• Advanced AI Framework Knowledge: Proficiency in multiple AI frameworks, including PyTorch,Tensorflow, with the ability to leverage these tools to develop and implement innovative AI solutions.
• Publication in Top‑Tier Journals: Experience publishing research findings in prestigious conferences and journals beyond the required top‑tier outlets, such as NIPS, CVPR, ICML, and ICLR, showcasing expertise in communicating complex research to technical audiences.
• Interdisciplinary AI Expertise: Deep expertise in multiple AI/ML areas, enabling the development of novel AI techniques and solutions that integrate concepts from diverse fields, such as computer vision, speech, NLP, and brain‑inspired algorithms.