# Applied Machine Learning Research Scientist

**Company:** [Cerebras Systems](https://hotfix.jobs/companies/cerebras-systems)
**Location:** Unspecified
**Role:** ML Engineering
**Experience:** 4+ years
**Skills:** Python, PyTorch, Transformers, LLMs, Reinforcement Learning, RLHF, rlvr, grpo, fsdp, megatron, machine learning pipelines, Data Pipelines, Distributed Training, Model Evaluation, synthetic data
**Posted:** 2026-03-05

> Build and optimize scalable machine learning systems for LLM pretraining, fine-tuning, alignment, and evaluation. The role requires 4+ years of ML systems experience, strong Python and PyTorch skills, and familiarity with transformers; experience with LLMs, reinforcement learning, and distributed training is preferred.

## Job Description

## Responsibilities
- Apply post-training techniques, including RLVR, RLHF, and 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 implementations.
- Design, implement, and scale ML pipelines across all stages of LLM development, including pretraining, fine-tuning, and 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.

## Requirements
- 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.
- 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 with large language models, including training, fine-tuning, and evaluation.
- Familiarity with reinforcement learning concepts.
- Experience with distributed training frameworks such as FSDP and 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
- Opportunity to build a breakthrough AI platform beyond the constraints of GPUs.
- Opportunities to publish and open-source cutting-edge AI research.
- Work on one of the fastest AI supercomputers in the world.
- Startup vitality with job stability.
- A non-corporate work culture that respects individual beliefs.

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**Apply:** https://hotfix.jobs/jobs/46587dc2-d0db-4e6e-b81a-5ef939ab89ef
**Canonical:** https://hotfix.jobs/jobs/46587dc2-d0db-4e6e-b81a-5ef939ab89ef