Applied Machine Learning Research Scientist

Summary

Cerebras Systems builds the world's largest AI chip, revolutionizing AI applications. As an Applied Machine Learning Research Scientist, you will develop scalable systems for large language models, collaborating with engineers and researchers to enhance model training and deployment processes.

Responsibilities

• Apply post-training techniques (e.g. RLVR, RLHF, GRPO etc.) techniques to improve model performance
• Build and maintain evaluation pipelines to measure model performance across tasks and domains
• Debug issues across the ML stack, including data pipelines, training jobs, model outputs and mixed or lower precision computation
• Collaborate with researchers to translate ML ideas into efficient, scalable implementation
• Design, implement, and scale ML pipelines across all stages of LLM development (pretraining, fine-tuning, alignment)
• Work with large datasets, including dataset generation, filtering, and synthetic data approaches
• Optimize training and inference workflows for performance, efficiency, and reliability
• Contribute high-quality, maintainable code to shared ML infrastructure

Skills

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 4+ years of experience (including internships, research, or industry experience) working with machine learning systems; we are hiring multiple positions for various levels
• Strong programming skills in Python
• Experience with ML frameworks such as PyTorch
• Solid understanding of machine learning fundamentals
• Familiarity with deep learning architectures, particularly transformers
• Ability to read and understand modern ML papers and implement key ideas
• Experience working with large language models (training, fine-tuning, and evaluation)
• Familiarity with reinforcement learning concepts
• Experience with distributed training frameworks (e.g., FSDP, Megatron)
• Experience working with large-scale datasets and data pipelines
• Experience debugging or optimizing ML systems for performance
• Contributions to meaningful codebases, projects, or open-source systems

Qualifications

Must Haves

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 4+ years of experience (including internships, research, or industry experience) working with machine learning systems; we are hiring multiple positions for various levels
• Strong programming skills in Python
• Experience with ML frameworks such as PyTorch
• Solid understanding of machine learning fundamentals
• Familiarity with deep learning architectures, particularly transformers
• Ability to read and understand modern ML papers and implement key ideas

Nice to Haves

• Experience working with large language models (training, fine-tuning, and evaluation)
• Familiarity with reinforcement learning concepts
• Experience with distributed training frameworks (e.g., FSDP, Megatron)
• Experience working with large-scale datasets and data pipelines
• Experience debugging or optimizing ML systems for performance
• Contributions to meaningful codebases, projects, or open-source systems

Benefits

• Build a breakthrough AI platform beyond the constraints of the GPU.
• Publish and open source their cutting-edge AI research.
• Work on one of the fastest AI supercomputers in the world.
• Enjoy job stability with startup vitality.
• Our simple, non-corporate work culture that respects individual beliefs.
• Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer.
• We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.