Research Engineer - Foundation Models

7 Months ago • All levels • $150,000 PA - $300,000 PA
Research Development

Job Description

We are seeking a research engineer with exceptional technical expertise in training Generative AI models. You will join our research team to develop core multimodal foundation models and manage large-scale GPU training runs. Your responsibilities will include leading research in multimodal foundation models, designing and experimenting with novel algorithms and architectures, optimizing model performance for production environments, inspecting and managing large data clusters to identify bottlenecks, and collaborating with cross-functional teams.
Good To Have:
  • Familiarity with Linux clusters and scripting.
  • Experience with large distributed systems (>100 GPUs).
Must Have:
  • Strong Python and PyTorch engineering skills.
  • Experience building ML models from scratch in PyTorch.
  • Familiarity with generative multimodal models and deep learning.
  • Knowledge of Transformers.
  • Lead research in multimodal foundation models.
  • Optimize model performance for production.
  • Inspect large data clusters for inefficiencies.
Perks:
  • Competitive equity packages in the form of stock options
  • Comprehensive benefits plan

Add these skills to join the top 1% applicants for this job

cross-functional
linux
pytorch
deep-learning
python
algorithms

We are looking for research engineer with extremely strong technical experience in training Generative AI models. You’ll be part of the research team, helping build our core multimodal foundation models and manage training runs across thousands of GPUs.

Responsibilities

  • Lead and contribute to cutting-edge research in multimodal foundation models

  • Design, develop, and experiment with novel algorithms, architectures, and techniques that enhance the performance, efficiency, and scalability of our AI models.

  • Optimize the performance of models for deployment in production environments, focusing on latency, throughput, and computational efficiency without compromising accuracy or robustness.

  • Inspect and manage large-scale data clusters to find inefficiencies and bottlenecks in model training, and data loading

  • Collaborate with cross-functional teams including data, applied research and infrastructure

Experience

  • Very strong demonstrated engineering ability in Python and Pytorch.

  • Experience building ML models from scratch in Pytorch.

  • Academic or Professional experience with (and understanding of) generative multimodal models such as Diffusion Models and GANs, as well as deep learning concepts such as Transformers.

  • Good to have familiarity with Linux clusters, systems & scripting.

  • Good to have experience working with large distributed systems (>100 GPUs).

Compensation

  • The pay range for this position in California is $180,000 - $250,000yr; however, base pay offered may vary depending on job-related knowledge, skills, candidate location, and experience. We also offer competitive equity packages in the form of stock options and a comprehensive benefits plan. 

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