Inception

Member of Technical Staff, Training

San Mateo, USA · Staff+

Sponsorship not specifiedDetected 135 days ago

Machine LearningDeep LearningPyTorchNLPLLMsResearch

About the role

We seek experienced scientists and engineers with deep expertise in pre-, mid-, and post- training large language models.

Design, develop, and optimize architectures for diffusion-based language models.
Implement innovative training objectives and loss functions for discrete diffusion LLMs.
Research and implement techniques for controlled text generation and constraint satisfaction.
Develop methods for multi-modal integration within the diffusion framework.
Improve model efficiency, reduce training time, and optimize inference throughput.
Develop and implement post-training techniques to align and improve model behavior.
Background in optimization theory and neural network architecture design.

The Role We seek experienced scientists and engineers with deep expertise in pre-, mid-, and post- training large language models.
BS/MS/PhD in Computer Science or a related field (or equivalent experience).
At least 2 years of experience working on ML projects in PyTorch (or equivalent), preferably in a research lab or engineering role.
Familiarity with training and inference in diffusion models.
Preferred Skills Extensive experience training transformer-based language models from scratch.
Knowledge of advanced training techniques (mixed precision, gradient accumulation, etc.).
Experience with LLM serving frameworks like vLLM, SGLang, or TensorRT.

Excellent familiarity with transformers and core LLM concepts (autoregressive pretraining, instruction tuning, in-context learning, KV caching).
Experience training deep learning models at scale in distributed computing environments.
Experience with multi-modal learning and cross-modal architectures.

This listing is sourced directly from Inception's careers page and normalized into a canonical job model.