5-7 years of experience in machine learning or related fields
Strong engineering skills for building robust systems
Fast learner with eagerness to explore and implement new concepts
Excellent team communication and collaboration capabilities
Deep understanding of model training pipelines and experimental methodologies
Responsibilities
Lead large-scale training runs and optimize model parallelization
Enhance performance of the pretraining architecture
Collect, process, and evaluate datasets for training
Conduct research on architecture methodologies and optimizer tests
Benefits
Comprehensive medical, dental, vision, and FSA plans
401(k) with competitive compensation structure
Relocation and immigration support as needed
Complimentary on-site meals from an in-house culinary team
Dynamic in-person work environment located in San Francisco, CA
Full Job Description
The Role:
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.
You'll Work Across:
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
What We're Looking For / 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
Qualifications / Additional Skills:
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)
Benefits and Perks:
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
