# Applied AI/ML Scientist

**Company:** [Cerebras Systems](https://hotfix.jobs/companies/cerebras-systems)
**Location:** Unspecified
**Role:** AI Research
**Skills:** Python, PyTorch, Deep Learning, Transformers, Mixture-Of-Experts, Multimodal Models, Sequence Models, Scaling Laws, LLMs, Supervised Fine-Tuning, RLHF, Dpo, Distributed Training, Data Processing, Agentic Systems
**Posted:** 2026-01-14

> Develops and customizes large language and deep learning models for customer-specific applications, owning training, fine-tuning, evaluation, and agentic-system development. Requires advanced graduate education, hands-on experience with 1B+ parameter models, Python, PyTorch, and distributed training.

## Job Description

## Responsibilities

### Customer Use Case Discovery & Project Scoping
- Collaborate with customer stakeholders to identify AI approaches for business problems.
- Contribute to engagement scoping, including feasibility analysis, data quality and readiness assessments, and model architecture selection.
- Define project milestones, success metrics, and evaluation benchmarks.

### Custom Models and AI Systems
- Architect and execute end-to-end training recipes for customer-specific models.
- Design adaptation strategies including continuous pre-training, supervised fine-tuning (SFT), and post-training alignment with RLHF or DPO.
- Own training pipelines from data preprocessing and tokenization through hyperparameter tuning and loss-curve analysis.
- Analyze model convergence, loss dynamics, and gradient stability on specialized hardware.
- Scale training workloads across Cerebras clusters for multi-billion-parameter models.
- Build and optimize agentic-system components focused on tool use, long-context reasoning, and multi-step planning.

### Technical Customer Leadership
- Serve as an AI/ML subject-matter expert during technical deep dives.
- Translate customer requirements into precise training recipes.
- Build strong customer relationships and communicate technical results to executives and research scientists.

### Internal Research and Engineering Collaboration
- Represent customer needs to internal R&D and engineering teams.
- Partner with ML and product teams on model architectures, training recipes, and case studies.
- Create internal playbooks from successful customer projects.

## Requirements
- Master’s or PhD in Computer Science, Machine Learning, or a related field.
- Expert understanding of dense transformers, mixture-of-experts models, multimodal models, sequence models, scaling laws, and training dynamics.
- Proven experience training or fine-tuning large models with 1B+ parameters.
- Mastery of Python and PyTorch.
- Experience with distributed training frameworks and large-scale distributed data-processing pipelines and tools.
- Strong interpersonal and communication skills.
- Ability to work autonomously and collaboratively in a fast-paced, dynamic environment.
- Ability to manage multiple projects and adapt as customer needs evolve.

## Benefits
- Work on a breakthrough AI platform and one of the fastest AI supercomputers in the world.
- Opportunities to publish and open-source AI research.
- Startup vitality with job stability.
- Non-corporate work culture focused on individual beliefs, learning, growth, and support.

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