Member of Technical Staff (GPU Performance Engineer)
Reka AI · US, UK, Singapore, Remote
Frontier labremote
At a glance
Highlights
- Design improvements to training infrastructure to optimize model performance.
- Work on post-training processes including reinforcement learning and fine-tuning.
- Improve efficiency and scalability of model serving infrastructure.
What they offer
- Five weeks of paid leave
- Comprehensive healthcare benefits including vision and dental
Ideal candidate
An experienced engineer passionate about large-scale model training and squeezing maximum performance from GPU systems, who thrives on deep technical ownership and optimizing frontier models.
Requirements
- Strong engineering skills with fluency in Python and PyTorch (or other frameworks)
- Proven experience implementing and training large deep learning models
- Experience writing and debugging low-level GPU code (CUDA, C++)
- Experience scaling up GPU jobs using large-scale compute clusters (e.g., Slurm or Kubernetes)
- Demonstrated ability to analyze and optimize performance of GPU-accelerated workloads, including profiling, identifying bottlenecks and implementing tuning techniques
- remote policy
- remote-first
- visa sponsorship
- Visa assistance including H1B and OPT transfers for US employees
Lab profile
About Reka AI
AI research lab building frontier multimodal models and physical-world intelligence for robotics and enterprise.
What they build
- Reka Core, Flash and Edge multimodal models
- Applied AI solutions for enterprise deployment
- Claru data marketplace for frontier and robotics labs
Known for
- Frontier multimodal model development
- Productionizing AI for real-world use
- Petabyte-scale data processing
- GPU performance engineering
Key facts
- Founded in 2022
- Headquartered in San Francisco
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