Zyphra
Research Engineer - Language Model Pre-Training
3mo ago
USASeniorpytorchpythondistributed systemsmachine learningdata processingmodel training
Research Engineer role focusing on language model pre-training and optimization at an AI company.
Responsibilities
- As a Research Engineer - Language Model Pre-Training , you'll shape our language model roadmap through end-to-end pretraining development. You will work extremely closely with our pretraining team, who will integrate your insights into our next-generation models.
Requirements
- Strong engineering aptitude for rapidly implementing reliable and robust systems
- Can rapidly learn new fields and are excited to implement new ideas
- Excellent communication and collaboration skills, and can work effectively on both research and engineering implementation at scale
- Deep expertise and intuition for solving machine learning problems and training models
- Experience with training on large-scale (multi-node) GPU clusters
- Deep understanding of model training pipelines – including model/data parallelism, distributed optimizers, etc.
- Strong grasp of proper experimental methodology for running rigorous ablations and other hypothesis testing
- Understanding of large-scale, highly parallel data processing pipelines
- High proficiency with PyTorch and Python.
- Strong ability to dive into large pre-existing codebases and rapidly get up to speed
- Published machine learning research in well-respected venues is a plus
- Postgraduate degree in a scientific subject (Computer Science, EE/EECS, Math, Physics)
Conditions
- Comprehensive medical, dental, vision, and FSA plans
- Competitive compensation and 401(k) plan
- Relocation and immigration support on a case-by-case basis
- In-office snacks and meals provided
- Unlimited PTO and company holidays
- In-person team in San Francisco with a collaborative, high-energy environment
Other
- Large-scale training runs and model parallelization
- Performance optimization of our pretraining stack
- Dataset collection, processing, and evaluation
- Architecture and methodology research, including optimizer ablations
- Our research methodology is to make grounded, methodical steps toward ambitious goals. Both deep research and engineering excellence are equally valued
- We strongly value new and crazy ideas and are very willing to bet big on new ideas
- We move as quickly as we can; we aim to minimize the bar to impact as low as possible
- We all enjoy what we do and love discussing AI