ML Research Engineer
| Company | Cerebras |
|---|---|
| Location | Sunnyvale, CA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Master’s, PhD |
| Experience Level | Mid Level, Senior |
Requirements
- Master’s or PhD degree or equivalent.
- Strong grasp of machine learning theory, fundamentals, linear algebra, and statistics.
- Experience with machine learning frameworks, such as PyTorch and Jax.
- Strong track record of research success through relevant publications at top conferences or journals (e.g. ICLR, ICML, NeurIPS), or patents and patent applications.
Responsibilities
- Develop novel training algorithms that advance the state-of-the-art in model quality and compute efficiency.
- Develop novel network architectures that address foundational challenges in language and multi-modal domains.
- Co-design ML algorithms that take advantage of our unique hardware, and collaborate with engineers to co-design next-generation architectures.
- Design and run research experiments that show novel algorithms are efficient and robust.
- Analyze results to gain research insights, including training dynamics, gradient quality, and dataset preprocessing techniques.
- Publish and present research at leading machine learning conferences.
Preferred Qualifications
- Experience with state-of-the-art transformer language models.
- Experience with distributed training concepts and frameworks, such as TorchTitan, Megatron/Deepspeed, or FairSeq FSDP.
- Experience with training speed optimizations, such as model architecture transformations to target hardware, or low-level kernel development (e.g., Triton).