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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.





Your role and responsibilities

We are seeking candidates with experience in training language models, including large-scale model development and optimization.
The role involves working across different stages such as pretraining, midtraining, and post-training refinement.
Familiarity with reinforcement learning (RL) techniques, particularly in model alignment or fine-tuning, is highly desirable.
Applicants should demonstrate a solid understanding of modern NLP frameworks and training pipelines.
Hands-on experience with scalable training infrastructure and experimentation workflows will be considered an advantage.





Required education
Bachelor's Degree

Preferred education
Master's Degree

Required technical and professional expertise
  • We are seeking candidates with experience in training language models, including large-scale model development and optimization.
  • The role involves working across different stages such as pretraining, midtraining, and post-training refinement.
  • Familiarity with reinforcement learning (RL) techniques, particularly in model alignment or fine-tuning, is highly desirable.
  • Applicants should demonstrate a solid understanding of modern NLP frameworks and training pipelines.
  • Hands-on experience with scalable training infrastructure and experimentation workflows will be considered an advantage.


Years of Experience:
2-6




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