Applied Machine Learning Research Scientist

Cerebras
United States, Canada
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 4+ yearsEducation: bachelorsSkills: []

Build and scale ML pipelines that train, fine-tune, and post-train large language models on an advanced AI platform. Apply reinforcement-learning-based post-training methods, design evaluation pipelines, and debug issues across data pipelines, training jobs, model outputs, and mixed/low-precision computation. Partner with researchers and engineers to translate ML ideas into efficient, reliable implementations using large datasets and optimization-focused training and inference workflows.

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FursaFursa
Cerebras
Cerebras
6 months ago

Applied Machine Learning Research Scientist

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Last checked: 16 hours agoStatus: Live

Job Summary

Build and scale ML pipelines that train, fine-tune, and post-train large language models on an advanced AI platform. Apply reinforcement-learning-based post-training methods, design evaluation pipelines, and debug issues across data pipelines, training jobs, model outputs, and mixed/low-precision computation. Partner with researchers and engineers to translate ML ideas into efficient, reliable implementations using large datasets and optimization-focused training and inference workflows.
Location: United States, Canada
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Apply post-training techniques (e.g., RLVR, RLHF, GRPO) 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 LLM stages (pretraining, fine-tuning, alignment) and optimize training/inference workflows for performance and reliability.

Key Requirements

  • •Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • •4+ years of experience working with machine learning systems (including internships, research, or industry experience).
  • •Strong programming skills in Python.
  • •Experience with ML frameworks such as PyTorch.
  • •A solid understanding of machine learning fundamentals and deep learning architectures, particularly transformers.
Experience:4+ yearsMachine learningDeep learningLarge language modelsReinforcement learningDistributed training
Education:Bachelor's in Computer Science, Engineering, or related field
Tech Stack:PythonPyTorchTransformersRLVRRLHFGRPOFSDPMegatron

Company Brief

Cerebras
Designs and builds wafer-scale AI accelerators and systems for large-scale deep learning workloads, delivering specialized hardware and software to accelerate model training and inference for enterprises and research institutions.
Industry: Hardware Devices
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Headquarters: Sunnyvale, United States
Founded: 2016
WebsiteLinkedIn